# Image-to-Pixel 3.1 Review: Turn Images and Videos Into Pixel Art for Free

Explore Image-to-Pixel 3.1, a free open-source converter featuring 16 dithering methods, 24 palettes, video-to-pixel-art tools, and sprite sheet exports.

Canonical URL: https://aiidelist.com/blog/image-to-pixel-3-1-review-guide

Language: en

Published: 2026-10-17

Updated: 2026-10-17

## Key Takeaways

- **Image-to-Pixel 3.1** is a free, open-source browser tool that converts photographs, illustrations, and videos into retro pixel art without requiring a generative AI model.
- The editor provides **16 dithering methods, 24 built-in color palettes, custom palette extraction, batch image conversion, and WebGL 2 acceleration**.
- Version **3.1.0** adds soundtrack preservation for supported MP4 and WebM exports, sharper video output, file renaming, and local project persistence.
- Game developers can export indexed PNGs, sprite sheets with JSON atlases, and deduplicated tilesets for use in game projects.
- The processing engine is available through the `image-to-pixel` npm package, enabling developers to build their own image conversion applications.
- Images and videos are processed locally in the official browser editor. Source files do not need to be uploaded to a remote image-generation service.
- **The best results depend on choosing the right resolution, palette, and dithering method.** Photographs, game sprites, and videos benefit from different processing settings.

## What Is Image-to-Pixel?

[Image-to-Pixel](https://tezumie.github.io/Image-to-Pixel/) is an open-source pixel art converter developed by Tezumie. It transforms existing images and videos into low-resolution artwork using color quantization, dithering, image resampling, and GPU-accelerated processing.

The project includes two primary components:

1. **An online pixel art editor:** A visual application for converting images, customizing pixel art styles, and exporting finished artwork.
2. **A JavaScript processing library:** A reusable engine that developers can integrate into websites, creative tools, and game development workflows.

The [online editor](https://tezumie.github.io/Image-to-Pixel/editor/) runs in a modern web browser and provides interactive controls for pixel size, color palettes, dithering, image adjustments, outlines, and export formats.

Unlike traditional AI image generators, Image-to-Pixel does not synthesize a new scene from a text prompt. Instead, it transforms the actual pixel data of an existing image according to specified processing rules.

For example, a developer can import a high-resolution character illustration, reduce it to a 64-pixel-wide image, apply a 16-color palette, and export a crisp pixel art sprite.

Similarly, a video creator can import footage, apply a consistent retro visual style across its frames, and export a pixelated MP4 or WebM video.

This combination of interactive editing, animation support, and programmable processing makes Image-to-Pixel more versatile than a basic pixelation filter.

As documented in October 2026, the official project website identifies **Image-to-Pixel 3.1.0** as its current release.

## Image-to-Pixel 3.0 vs. 3.1: What's New?

Image-to-Pixel 3.0 introduced a substantially redesigned editor and processing architecture.

The update expanded the project beyond basic image conversion with additional dithering methods, palette management, video processing, batch conversion, sprite sheets, and GPU acceleration.

Version 3.1 focuses primarily on improving video workflows, project management, and output compatibility.

| Feature | Image-to-Pixel 3.0 | Image-to-Pixel 3.1 |
| --- | --- | --- |
| Editor interface | Redesigned three-panel interface | Retains the new interface with usability improvements |
| Processing engine | WebGL 2 with CPU fallback | Same core processing architecture |
| Dithering | 16 methods plus no-dither mode | Retains the full dithering system |
| Built-in palettes | 24 palettes | Retains the palette collection |
| Batch processing | Shared and per-file settings | Retains batch processing and adds improved persistence |
| Video export | GIF, WebM, MP4, and PNG sequences | Enhanced video export with optional audio |
| Soundtrack preservation | Not included in standard video export | Supported in compatible MP4 and WebM exports |
| Video sharpness | Pixelated video output | Integer-scaled video encoding |
| File naming | Basic file management | File renaming through the editor |
| Saved projects | Settings and preset persistence | Open files, names, and settings saved through IndexedDB |
| Video muxing | External muxer packages | Project-maintained MP4 and WebM muxers |

According to the [official changelog](https://tezumie.github.io/Image-to-Pixel/docs/changelog/), version 3.1 also improves playback looping for certain MOV and MP4 files.

### Why the 3.1 update matters

The addition of audio support significantly improves the usefulness of video-to-pixel-art conversion.

Previously, users creating pixelated videos often needed a separate editing application to restore the original soundtrack.

The newer version can retain audio when exporting supported MP4 and WebM files. The soundtrack is trimmed to match the selected video segment.

Another improvement concerns scaling. Small pixel-art frames can become blurry when video players enlarge them through interpolation.

Image-to-Pixel 3.1 can enlarge frames by whole-number scaling before encoding, helping preserve the intended square pixel structure during playback.

Together, these improvements make the tool more practical for producing finished retro videos instead of only short visual experiments.

## Image-to-Pixel Features Explained

| Feature | Description | Main benefit |
| --- | --- | --- |
| Image pixelation | Reduces images into controlled pixel grids | Retro graphics and portraits |
| 16 dithering methods | Uses ordered patterns and error diffusion | Different pixel art appearances |
| 24 built-in palettes | Provides predefined limited-color schemes | Consistent artistic styles |
| Custom color palettes | Imports or manually defines palette colors | Brand and game visual consistency |
| Palette extraction | Extracts representative colors from images | More faithful source-image conversion |
| Batch processing | Converts multiple images using shared or individual settings | Efficient asset production |
| Video pixelation | Applies effects across video frames | Retro animations and short videos |
| Audio-preserving export | Retains sound in supported video formats | More complete video workflows |
| Indexed PNG export | Encodes limited-color images using PNG palettes | Smaller image files in suitable cases |
| Sprite sheet export | Packs frames into an image with JSON metadata | Game animation assets |
| Tileset generation | Extracts reusable square tiles | Tile-based game development |
| WebGL 2 processing | Executes image transformations through shaders | Responsive interactive editing |
| CPU fallback | Processes images without GPU acceleration | Broader runtime compatibility |
| JavaScript API | Provides programmatic access to conversion | Custom applications and pipelines |

The editor also includes cropping, color adjustments, outlines, cleanup filters, zooming, before-and-after comparison, presets, and shareable settings.

## How to Convert an Image Into Pixel Art Online

Image-to-Pixel can be used without registering an account or installing desktop software.

The following workflow provides a practical method for producing recognizable pixel art from an existing photograph or illustration.

### Step 1: Open the online editor

Visit the [Image-to-Pixel editor](https://tezumie.github.io/Image-to-Pixel/editor/).

The interface is divided into three areas:

- **Library:** Files, presets, and color palettes.
- **Canvas:** Original and processed image previews, zooming, and visual comparison.
- **Inspector:** Pixel dimensions, processing settings, color adjustments, and exports.

Users can import images by dragging files into the editor, choosing a local file, or pasting an image from the clipboard.

Supported image inputs include PNG, JPEG, WebP, SVG, AVIF, BMP, and GIF first frames, subject to browser decoding support.

### Step 2: Choose the output pixel resolution

The output resolution determines how many pixels represent the artwork.

Smaller dimensions create stronger pixelation but remove more detail.

| Pixel width | Recommended application | Expected appearance |
| --- | --- | --- |
| 16–32 pixels | Small icons and simple sprites | Very chunky, minimal detail |
| 32–64 pixels | Game characters and avatars | Strong retro appearance |
| 64–128 pixels | Portraits and illustrations | Balanced detail and pixelation |
| 128–256 pixels | Detailed scenes and backgrounds | More recognizable source detail |
| 256–512 pixels | Large images and subtle effects | Less pronounced pixelation |

These values are practical starting points rather than fixed requirements.

For example, a simple character silhouette might remain recognizable at 32 pixels, while a photograph containing several people may need a considerably larger grid.

The editor also supports defining pixel size relative to the source image.

A 960-pixel-wide image processed with a source block size of eight pixels becomes approximately 120 pixels wide.

### Step 3: Choose the resampling method

Image-to-Pixel offers two primary resampling approaches.

**Average resampling** combines source pixels into representative output colors. It generally works well for photographs, gradients, and smooth illustrations.

**Nearest-neighbor resampling** selects source pixels without blending. It is useful when processing existing pixel art or graphics with deliberate hard edges.

Using average resampling on an already pixelated sprite can introduce unwanted intermediate colors. Conversely, using nearest-neighbor resampling on detailed photography may retain distracting high-frequency patterns.

The appropriate choice depends on the source material.

### Step 4: Select a color palette

Open the palette controls and select a built-in palette, import a custom palette, or extract colors directly from the source image.

For retro game artwork, a compact predefined palette such as PICO-8 or Sweetie 16 provides recognizable stylistic constraints.

For photography, extracting representative colors may preserve the original image's overall appearance more effectively.

### Step 5: Apply dithering

Dithering approximates unavailable colors by arranging existing palette colors into small patterns.

Common starting choices include:

- **Floyd–Steinberg:** Detailed photographs and organic gradients.
- **Bayer 4×4:** Structured retro graphics.
- **Blue noise:** Fine texture without obvious repeating patterns.
- **Atkinson:** High-contrast monochrome pixel art.
- **No dithering:** Flat-color icons and clean sprites.

Begin with moderate strength and adjust while observing the preview.

Excessive dithering can produce distracting noise around faces, lettering, and small objects.

### Step 6: Adjust contrast, color, and outlines

The editor provides controls for brightness, contrast, saturation, hue, gamma, and transparency.

Additional processing options include isolated-pixel removal, majority smoothing, and inner or outer outlines.

These features can improve the readability of small artwork, but aggressive cleanup may remove deliberate details.

Use the comparison view to check whether important shapes remain recognizable.

### Step 7: Export the result

Choose PNG export and the desired output scale.

Integer scaling preserves hard pixel edges when enlarging the image.

For example, a 128×128 image exported at 4× becomes a 512×512 image in which each original pixel is represented by a 4×4 block.

The enlarged image remains based on a 128×128 pixel grid. Scaling does not restore details removed during conversion.

The [getting-started documentation](https://tezumie.github.io/Image-to-Pixel/docs/getting-started/) provides additional instructions and keyboard shortcuts.

## Understanding the 16 Dithering Methods

Dithering is one of the most important technical features in Image-to-Pixel.

When a source image contains millions of possible colors but the output palette contains only 16, 32, or 64 colors, many original shades cannot be represented directly.

Dithering compensates by placing available palette colors into patterns that approximate intermediate tones.

Image-to-Pixel offers 16 dithering methods, plus the option to disable dithering.

### Ordered dithering

Ordered dithering uses predetermined threshold patterns.

Available methods include Bayer 2×2, Bayer 4×4, Bayer 8×8, Bayer 16×16, clustered-dot 4×4, clustered-dot 8×8, horizontal lines, blue noise, and custom matrices.

Because ordered dithering evaluates pixels using stable thresholds, it generally produces predictable patterns across animation frames.

This makes it useful for video conversion and retro game aesthetics.

### Error-diffusion dithering

Error diffusion distributes quantization errors into neighboring pixels.

When one pixel is assigned a palette color, the difference between that color and the original value influences neighboring pixels.

Image-to-Pixel includes Floyd–Steinberg, Atkinson, Sierra Lite, Sierra, Burkes, Jarvis–Judice–Ninke, and Stucki methods.

These approaches can reproduce gradients and photographic detail more naturally, but their patterns can change substantially between adjacent animation frames.

### Dithering comparison

| Method | Appearance | Best application | Main drawback |
| --- | --- | --- | --- |
| None | Solid color blocks | Icons and clean sprites | Visible color banding |
| Bayer 2×2 | Coarse geometric texture | Tiny retro graphics | Strong repetitive pattern |
| Bayer 4×4 | Traditional ordered pixels | Retro portraits | Visible crosshatching |
| Bayer 8×8 | Finer structured texture | Detailed illustrations | Mechanical appearance |
| Bayer 16×16 | Complex ordered gradients | Larger retro artwork | Dense patterns |
| Clustered dot | Halftone-style dots | Posters and print effects | Less suitable for tiny sprites |
| Horizontal lines | Scan-line patterns | Stylized retro visuals | Directional texture |
| Blue noise | Fine irregular grain | Video and backgrounds | Can appear noisy |
| Floyd–Steinberg | Organic dispersed pixels | Photographs | Animation shimmer |
| Atkinson | Light, high-contrast diffusion | Monochrome artwork | Less faithful tonal reproduction |
| Sierra Lite | Compact diffusion texture | General illustrations | May lose delicate details |
| Sierra | Smoother error diffusion | Gradients | More visual texture |
| Burkes | Distributed tonal transitions | Detailed illustrations | Small features may soften |
| Jarvis–Judice–Ninke | Wide error distribution | Complex photographic gradients | Dense diffusion patterns |
| Stucki | Smooth distributed errors | Larger images | Less ideal for clean sprite edges |

### Why Floyd–Steinberg works well for photographs

Floyd–Steinberg distributes quantization errors across neighboring pixels using a small weighted kernel.

This allows a limited palette to preserve the overall appearance of gradients without requiring a unique palette color for every source shade.

It is particularly effective when photographic detail matters more than strict geometric patterns.

However, its output depends on previous pixel decisions. A small change in one area can influence surrounding pixels.

In animation, these differences can appear as flicker or shimmering.

### Why Bayer and blue noise work better for animation

Ordered dithering uses fixed threshold patterns rather than propagated errors.

When the input changes between frames, the pattern does not depend on a changing chain of error accumulation.

This helps maintain more stable visual texture.

For animated pixel art, Bayer 4×4 and blue noise are useful starting points.

The [official dithering reference](https://tezumie.github.io/Image-to-Pixel/docs/dithering/) documents the algorithms and strength controls.

## Color Palettes: 24 Built-In Options and Custom Colors

A limited palette is central to recognizable pixel art.

Reducing image resolution without controlling colors often produces a pixelated photograph rather than artwork resembling a carefully designed retro game.

Image-to-Pixel provides 24 built-in palettes covering classic game-inspired colors, monochrome looks, and more elaborate artistic schemes.

Examples include:

- **PICO-8:** A compact 16-color palette associated with retro game development.
- **Game Boy DMG:** A four-color green-toned aesthetic.
- **Endesga 32:** A versatile 32-color palette for colorful artwork.
- **Sweetie 16:** A compact palette suitable for character graphics and illustrations.
- **Resurrect 64:** A larger palette providing additional color flexibility.
- **Grayscale 4:** Four shades suitable for monochrome graphics.
- **1-Bit Monitor:** A two-color appearance for high-contrast images.

Additional built-in palettes are documented in the [palette reference](https://tezumie.github.io/Image-to-Pixel/docs/palettes/).

### Custom palette support

The editor supports importing several palette formats:

| Format | Typical use |
| --- | --- |
| `.gpl` | GIMP and compatible graphics applications |
| `.hex` | Hexadecimal color lists |
| `.pal` | JASC-PAL-compatible palettes |
| `.txt` | Supported plain-text color definitions |
| `.json` | Structured palette definitions |

Users can also manually add colors or select colors from the original image.

The editor supports retrieving palettes from [Lospec](https://lospec.com/palette-list), an online library of pixel art palettes.

Online palette retrieval requires network access, while local image processing does not.

### Automatic palette extraction

Image-to-Pixel can derive representative colors from a source image.

The engine uses median-cut clustering followed by k-means refinement to produce a smaller palette reflecting the original color distribution.

This is useful when converting photographs with distinctive color schemes.

For example, a sunset photograph may contain hundreds of orange, purple, and red variations. Palette extraction can reduce those into a manageable set while retaining the scene's overall atmosphere.

However, extracted palettes are not automatically equivalent to artist-designed palettes.

A handcrafted palette may provide stronger consistency across multiple characters, environments, or animation frames.

### OKLab vs. RGB color matching

Image-to-Pixel uses OKLab as its default color-matching space.

OKLab is designed to represent perceptual color differences more evenly than simple RGB channel distance.

This can help when selecting the closest available palette color for a source pixel.

RGB matching is also available and may produce desirable results for certain limited palettes.

The best choice depends on the source and desired artistic style. Comparing both modes on the same image is more informative than assuming one is universally superior.

## How to Convert Video Into Pixel Art

Image-to-Pixel can process supported video files frame by frame, allowing creators to transform ordinary footage into retro pixel animations.

Supported input containers include MP4, WebM, and MOV when their codecs are supported by the browser.

### Step-by-step video conversion

1. Open the online editor and import a compatible video.
2. Select a pixel width appropriate for the subject and output format.
3. Choose a consistent palette for the clip.
4. Apply Bayer or blue-noise dithering to reduce temporal shimmer.
5. Preview playback and inspect individual frames.
6. Select the start time, end time, and export frame rate.
7. Choose GIF, WebM, MP4, or PNG sequence output.
8. Enable audio preservation when using a supported video format.
9. Select the final video size and export the result.

### Video export formats compared

| Format | Video encoding | Audio | Best use case |
| --- | --- | --- | --- |
| GIF | Animated image | No | Short looping animations |
| WebM | VP9 or VP8 through WebCodecs | Opus when supported | Browser playback |
| MP4 | H.264 through WebCodecs | AAC or Opus when supported | General video distribution |
| PNG sequence | Individual PNG frames | No | Editing and game assets |

### How Image-to-Pixel preserves video audio

Version 3.1 can retain the original soundtrack when exporting supported MP4 and WebM videos.

The editor decodes the source audio and re-encodes it for the selected output format.

The soundtrack is trimmed to match the exported video range, and multichannel audio can be mixed down to stereo.

MP4 uses AAC when supported by the browser. Other environments may encode Opus audio inside the MP4 container.

This matters because some players, including QuickTime and Windows Media Player, may not support that combination reliably.

WebM with Opus audio may provide a more compatible alternative in those environments.

If the browser cannot decode the source audio or encode a suitable output codec, the video may still be exported without sound.

### Why video export can be slow

The converter processes requested frames individually rather than depending on ordinary real-time video playback.

This approach helps prevent skipped or duplicated frames caused by slow processing.

However, a longer clip or higher frame rate requires more frames to be decoded, transformed, and encoded.

A four-second video exported at 24 frames per second requires approximately 96 processed frames.

A 60-second clip at the same frame rate requires approximately 1,440 frames.

Processing demands also depend on source resolution, output resolution, dithering method, encoding settings, and device capabilities.

### Why integer scaling improves pixel video quality

Consider converting a 1920×1080 video into pixel art at 160×90 pixels.

The reduced frame contains only 14,400 pixels.

If exported directly at that size, a player may enlarge it using smooth interpolation, causing blurry edges.

Applying 12× nearest-neighbor scaling produces a 1920×1080 frame in which each original pixel becomes a 12×12 block.

The video remains visually based on 160×90 pixels, but the encoded frame preserves sharper pixel boundaries.

Version 3.1 supports whole-number scaling for WebM and MP4 output, with size options including approximately Full HD, 720p, and 4K where supported.

The [official video documentation](https://tezumie.github.io/Image-to-Pixel/docs/video/) explains audio, frame processing, codec support, and export limitations.

## Sprite Sheets and Tilesets for Game Developers

Image-to-Pixel includes several features particularly useful for independent game development.

### Sprite sheet generation

A sprite sheet combines multiple animation frames into a single image.

The editor can convert frames using shared or independent settings, arrange them in a grid, and export an accompanying JSON atlas.

The atlas follows a TexturePacker-style hash structure that compatible game-engine import workflows can interpret.

Users can configure the number of columns and padding between frames.

This is useful for preparing existing animations for frameworks and engines such as Phaser, PixiJS, or compatible Godot importers.

However, sprite sheet export does not generate missing animation frames or automatically correct inconsistent character proportions.

### Tileset generation

The editor can divide processed artwork into square tiles ranging from 8 to 64 pixels.

Repeated tiles are deduplicated, and a JSON map records which tiles appear in each position.

Optional mirrored-tile detection can also recognize horizontally or vertically flipped versions of existing tiles.

This is useful for prototyping tile-based backgrounds, terrain patterns, and repeating environmental elements.

The exported tile map does not automatically provide collision geometry, navigation paths, or level logic.

Those systems must be implemented in the target game engine.

### Batch asset processing

Users can import multiple images and apply shared conversion settings.

Individual images can also receive independent settings where specific cropping or adjustments are required.

Batch output is packaged as a ZIP containing processed PNG files and settings information.

A practical game-development workflow is to select a shared palette first, convert the asset collection, and then manually refine important sprites.

The [export documentation](https://tezumie.github.io/Image-to-Pixel/docs/export/) explains the available image, animation, sprite sheet, and tileset options.

## How Image-to-Pixel Works: WebGL 2 and GPU Processing

Image-to-Pixel uses a structured image-processing pipeline rather than a generative model.

The core stages include:

1. **Preparation:** Resample the source image and apply tonal or transparency adjustments.
2. **Color quantization:** Map source pixels to the available palette colors.
3. **Dithering:** Apply ordered thresholds or distribute quantization errors.
4. **Color resolution:** Convert palette indices into final pixel colors.
5. **Cleanup:** Optionally remove isolated pixels or apply majority smoothing.
6. **Outlining and export:** Add selected outlines and generate output files.

The GPU implementation uses WebGL 2 fragment shaders through ShaderMate.

A corresponding CPU implementation provides an alternative processing path when WebGL is unavailable or unsuitable.

### GPU acceleration for error diffusion

Error diffusion is challenging to parallelize because the output of one pixel depends on errors propagated from previously processed pixels.

Image-to-Pixel addresses this using a **diagonal wavefront algorithm**.

Pixels are processed in groups whose dependencies have already been resolved.

This enables the GPU to perform parts of the diffusion process in parallel while respecting the underlying algorithm's dependency structure.

The project documents matching GPU and CPU results, with tests comparing processing outputs.

### GPU vs. CPU limitations

GPU processing is not automatically faster in every environment.

Some devices use software-rendered WebGL implementations, which may be inefficient for repeated diffusion passes.

The automatic backend can use CPU processing when appropriate.

The editor also limits oversized source inputs. Images larger than 4096 pixels on either side are reduced before normal processing.

This helps control memory use without requiring full-resolution processing for low-resolution artwork.

The [technical documentation](https://tezumie.github.io/Image-to-Pixel/docs/how-it-works/) describes the shader architecture and processing pipeline.

## How to Use Image-to-Pixel in JavaScript

The image-processing library is published as an npm package named `image-to-pixel`.

Developers can use it to create their own online pixel art tools, asset processors, or interactive editing applications.

### Install the package

```bash
npm install image-to-pixel
```

### Basic image conversion example

The following browser example converts an existing image element into pixel art:

```javascript
import { createPixelator } from 'image-to-pixel';

const image = document.querySelector('#source-image');
await image.decode();

const pixelator = await createPixelator({ backend: 'auto' });

try {
  const result = await pixelator.process(image, {
    size: { width: 128 },
    palette: {
      source: 'builtin',
      id: 'pico-8',
    },
    dither: {
      method: 'floyd-steinberg',
      strength: 0.8,
    },
  });

  const canvas = result.toCanvas(4);
  document.body.append(canvas);

  const png = await result.toBlob({ scale: 4 });
  console.log(png.size);
} finally {
  pixelator.destroy();
}
```

The example assumes that the source image has already been added to the page and is accessible through the `source-image` element ID.

The code performs four operations:

1. Initializes the processing engine.
2. Converts the source into a 128-pixel-wide image using the PICO-8 palette.
3. Applies Floyd–Steinberg dithering at 80% strength.
4. Produces an enlarged canvas and PNG blob.

The `destroy()` call releases processing resources after completion.

### Choosing a processing backend

The engine supports three backend configurations:

| Backend | Behavior |
| --- | --- |
| `auto` | Selects a suitable WebGL 2 or CPU processing path |
| `webgl` | Uses WebGL and fails when the backend is unavailable |
| `cpu` | Performs processing without GPU rendering |

For interactive browser applications, the automatic backend is generally the most convenient starting point.

### Processing images in Node.js

Image-to-Pixel can operate on RGBA pixel buffers in Node.js through its CPU backend.

A separate image-decoding library is required when reading formats such as JPEG or PNG from disk.

For example, Sharp can decode an image into raw RGBA data before passing it to the conversion engine.

```bash
npm install image-to-pixel sharp
```

A basic Node.js workflow can then decode, transform, and save an image:

```javascript
import sharp from 'sharp';
import { createPixelator } from 'image-to-pixel';
import { writeFile } from 'node:fs/promises';

const { data, info } = await sharp('input.jpg')
  .ensureAlpha()
  .raw()
  .toBuffer({ resolveWithObject: true });

const pixelator = await createPixelator({ backend: 'cpu' });

try {
  const result = await pixelator.process(
    {
      width: info.width,
      height: info.height,
      data,
    },
    {
      size: { width: 96 },
      palette: { source: 'builtin', id: 'pico-8' },
      dither: { method: 'bayer4', strength: 0.7 },
    }
  );

  const output = await result.toPNG({ scale: 4 });
  await writeFile('output.png', output);
} finally {
  pixelator.destroy();
}
```

This type of integration is useful for batch asset pipelines and custom image-processing services.

### Embedding the complete editor

Developers who need the full editing interface can use the documented `mountEditor()` API instead of building every control from scratch.

The embedded editor requires its stylesheet and an appropriately sized container.

Additional integration details are available in the [JavaScript library reference](https://tezumie.github.io/Image-to-Pixel/docs/library/) and [embedding documentation](https://tezumie.github.io/Image-to-Pixel/docs/embedding/).

## Recommended Pixel Art Settings for Different Styles

The following configurations provide useful starting points for common creative applications.

They are recommendations rather than experimentally verified universal presets.

| Desired style | Output width | Palette | Dithering | Additional adjustment |
| --- | --- | --- | --- | --- |
| Game Boy-style artwork | 64–160 px | Game Boy DMG | Atkinson or Bayer | Moderate contrast |
| Colorful character sprite | 32–64 px | Sweetie 16 | None or Bayer 2×2 | Optional outline |
| Detailed pixel portrait | 96–128 px | Endesga 32 | Floyd–Steinberg | Tight crop |
| Monochrome icon | 16–32 px | Two colors | None | Manual cleanup |
| Retro photograph | 128–256 px | Extracted 16–32 colors | Floyd–Steinberg | Average resampling |
| Pixel art video | 96–160 px | Fixed 16–32 colors | Bayer or blue noise | Integer scaling |
| Newsprint poster | 128–256 px | Grayscale | Clustered dot | Increased contrast |
| Clean game UI | 32–128 px | Custom palette | None | Crisp edges |

### Why the correct settings depend on the final display size

A 32-pixel-wide character displayed at 32 screen pixels looks very different from the same character displayed at 256 screen pixels.

At native size, individual pixels may be difficult to distinguish. At larger integer scales, the pixel structure becomes an intentional design feature.

Therefore, artwork should be evaluated at its intended display size rather than exclusively through a highly zoomed editor preview.

For game assets, it is also important to confirm how the target engine handles texture filtering.

Bilinear filtering can blur deliberate pixel boundaries even when the exported image itself is perfectly sharp.

## Image-to-Pixel vs. AI Pixel Art Generators

Image-to-Pixel and generative AI tools address different creative needs.

| Category | Main purpose | Advantages | Limitations |
| --- | --- | --- | --- |
| Image-to-Pixel | Transform existing images and videos | Predictable processing, palettes, local conversion, batch output | Cannot invent new compositions |
| Basic pixelation filters | Apply a blocky effect | Simple and fast | Limited dithering and export control |
| AI pixel art generators | Create artwork from prompts | Can invent characters and scenes | Source consistency and costs vary |
| Manual pixel art editors | Draw pixels directly | Maximum artistic control | More time-intensive |
| General image editors | Perform broad image editing | Flexible toolsets | Pixel art workflows may require additional setup |

### When Image-to-Pixel is the better choice

Image-to-Pixel is particularly useful when an existing image must retain its identity while receiving a consistent retro treatment.

For example, a developer converting a collection of character portraits can apply the same palette and output dimensions to every image.

A generative AI system might create a different interpretation of each character, even when provided with similar instructions.

### When generative AI is more appropriate

Generative AI can be useful when the desired image does not yet exist.

A prompt describing a fantasy castle, for example, requires content generation rather than straightforward image transformation.

One hybrid approach is to generate an initial illustration using an AI image model and then process that artwork through Image-to-Pixel for more consistent color constraints.

### Why manual pixel art still matters

Professional pixel art relies on intentionally designed shapes, silhouettes, outlines, and color clusters.

Automatic conversion may produce stray pixels, noisy shading, inconsistent outlines, or unclear expressions at very low resolutions.

For polished game assets, manual refinement may still be necessary after conversion.

## Common Image-to-Pixel Problems and Fixes

### 1. The exported pixel art looks blurry

The likely cause is smooth interpolation during enlargement or display.

Use integer nearest-neighbor scaling and disable smooth texture filtering in the destination application when possible.

For video, use the editor's integer-scaled output rather than exporting an extremely small frame and relying on the media player to enlarge it.

### 2. Important image details disappear

Increase the output resolution or crop closer to the main subject.

A photograph containing several faces cannot retain the same structural detail at 32 pixels as it can at 256 pixels.

Dithering helps approximate colors but cannot restore details lost during resampling.

### 3. Faces look noisy

Reduce dithering strength, select a more suitable palette, and increase the pixel width.

A limited palette with better separation between highlights and shadows can improve facial readability.

### 4. Video frames flicker

Switch from error diffusion to Bayer or blue-noise dithering.

Use a consistent palette and inspect adjacent frames to evaluate temporal stability.

### 5. MP4 exports have no sound

The browser may lack the required audio decoding or encoding support.

Try a compatible browser, check the source audio format, or export WebM where appropriate.

### 6. MP4 audio does not play in QuickTime

The MP4 file may contain Opus audio rather than AAC.

Some players do not support this combination reliably.

WebM export or separate audio transcoding may resolve the compatibility issue.

### 7. Video conversion is slow

Reduce the clip duration, output frame rate, or processing dimensions.

Long videos require many independently processed and encoded frames.

### 8. Saved projects disappear

Browser storage is not permanent cloud backup.

Clearing site data, using private browsing, or exceeding storage limits can remove locally saved files.

Export important artwork and settings separately.

### 9. Colors appear muddy

Compare OKLab and RGB color matching, adjust the palette, and reduce dithering strength.

For small sprites, a smaller carefully selected palette can improve clarity.

### 10. The output does not resemble handcrafted pixel art

Automatic conversion cannot make every artistic decision required for polished low-resolution artwork.

Improve the silhouette, remove unnecessary texture, adjust color clusters, and manually refine important features.

## Privacy, Licensing, and Commercial Use

### Does Image-to-Pixel upload source files?

The official editor processes images and videos locally in the browser.

Source files do not need to be sent to a remote server for conversion.

This can be beneficial when working with private photographs, unpublished artwork, or commercial game assets.

However, local image conversion should not be confused with a guarantee that every website interaction occurs offline.

For example, retrieving palettes from Lospec requires an internet connection.

Third-party applications built with the library may also implement their own upload, analytics, or storage systems.

### Is Image-to-Pixel open source?

Yes. The official [GitHub repository](https://github.com/Tezumie/Image-to-Pixel) identifies the project as MIT-licensed.

According to the current repository README, the MIT license covers the library, editor, website, and retained classic 2.x files.

The repository also credits external palette authors and identifies separate font licensing where applicable.

### Can Image-to-Pixel be used commercially?

The MIT license generally permits commercial use, modification, and redistribution, provided the required copyright and license notices are preserved.

However, the software license does not automatically grant rights to copyrighted source images, game characters, photographs, fonts, or third-party assets.

Commercial applications should verify the rights associated with their inputs and any external resources they redistribute.

## Frequently Asked Questions

### Is Image-to-Pixel free?

Yes. The official browser editor is free to use, and the underlying library is available as open-source software. Developers running their own applications may still incur ordinary hosting or infrastructure costs.

### Does Image-to-Pixel use artificial intelligence?

The core converter does not require generative AI. It uses conventional image-processing techniques including resampling, color quantization, dithering, and GPU shaders.

### Can Image-to-Pixel convert MP4 videos?

Yes, provided the browser can decode the source video's underlying codec. Supported exports include MP4, WebM, GIF, and PNG sequences.

### Can it preserve video audio?

Version 3.1 supports optional audio preservation in compatible MP4 and WebM exports. The exact audio codec and availability depend on browser capabilities.

### How many dithering methods are available?

The editor provides 16 dithering methods, including ordered patterns, error-diffusion algorithms, and custom matrices, plus a mode that disables dithering.

### Can Image-to-Pixel generate game sprites?

It can transform existing artwork and export sprite sheets or tilesets. It does not independently invent new characters or generate missing animation poses.

### Does Image-to-Pixel support transparent PNGs?

The editor supports transparency thresholding and PNG output. It does not automatically perform semantic background removal from complex photographs.

### Can the editor process multiple images at once?

Yes. Images can share settings or use individual adjustments, and processed batches can be exported as ZIP archives.

### Can Image-to-Pixel run in Node.js?

Yes. The processing engine supports a CPU backend that accepts decoded RGBA pixel buffers. Separate decoding may be required for source image files.

### Can it be embedded into another website?

Yes. Developers can integrate the image-processing library or use the documented editor embedding API.

### Does Image-to-Pixel work offline?

Core conversion does not require a remote processing service once the application code is available locally. The hosted editor may still require an initial network connection, and online palette retrieval requires connectivity.

### What is the best dithering method for video?

Bayer and blue-noise dithering are generally useful starting points because their stable threshold patterns reduce the frame-to-frame shimmer commonly associated with error diffusion.

### What is the best output resolution for pixel art portraits?

Approximately 64–128 pixels wide is a practical starting range for many portraits. The appropriate resolution depends on the composition, subject complexity, and intended display size.

## Conclusion

**Image-to-Pixel 3.1 is a capable free, open-source pixel art converter that combines accessible browser editing with sophisticated image-processing features.**

Its most significant strengths include 16 dithering methods, 24 built-in palettes, custom palette management, video conversion, batch processing, and game-ready export formats.

Version 3.1 improves the workflow for video creators through soundtrack preservation, sharper integer-scaled output, and local project persistence.

For developers, the JavaScript library provides a practical way to integrate pixel art processing into existing websites and applications without depending on a generative image API.

However, automatic pixelation is not a replacement for carefully designed pixel art. The best results still require appropriate resolution choices, consistent palettes, restrained dithering, and manual refinement when necessary.

For photographs, start with moderate resolution and Floyd–Steinberg dithering. For videos, prioritize Bayer or blue noise. For clean game sprites, focus on recognizable silhouettes and limited-color palettes.

**Try the [free Image-to-Pixel editor](https://tezumie.github.io/Image-to-Pixel/editor/)**, explore the [official documentation](https://tezumie.github.io/Image-to-Pixel/docs/), and review the [GitHub repository](https://github.com/Tezumie/Image-to-Pixel) to evaluate its capabilities for creative work or application development.