libimagequant-wasm

libimagequant-wasm

A TypeScript/JavaScript WebAssembly wrapper for the libimagequant image quantization library. This package provides high-quality image color quantization in the browser using Web Workers for optimal performance.

Features

• High-quality image quantization - Convert 24/32-bit images to 8-bit palette with alpha channel
• Web Worker support - Non-blocking image processing using Web Workers
• TypeScript support - Full TypeScript definitions included
• Promise-based API - Modern, easy-to-use async interface
• Optimized WASM - Size and performance optimized WebAssembly build
• Browser compatible - Works in all modern browsers supporting WebAssembly
• Multiple formats - Supports ESM and CommonJS

Installation

npm install libimagequant-wasm

Requirements

• Node.js >= 20.19.0
• Modern browser with WebAssembly and Web Worker support

Quick Start

Quantize a PNG

import LibImageQuant from 'libimagequant-wasm';

const quantizer = new LibImageQuant();

// Fetch a PNG and quantize it
const response = await fetch('image.png');
const pngData = new Uint8Array(await response.arrayBuffer());

const result = await quantizer.quantizePng(pngData, {
  maxColors: 64,
  quality: { min: 0, target: 100 },
  speed: 3,
});

console.log(`Quantized to ${result.paletteLength} colors`);
console.log(`Quality: ${Math.round(result.quality * 100)}%`);

// result.pngBytes - quantized indexed PNG as Uint8Array
// result.imageData - quantized image as ImageData (for canvas rendering)

quantizer.dispose();

Quantize from Canvas

import LibImageQuant from 'libimagequant-wasm';

const quantizer = new LibImageQuant();

const canvas = document.getElementById('myCanvas') as HTMLCanvasElement;
const ctx = canvas.getContext('2d')!;
const imageData = ctx.getImageData(0, 0, canvas.width, canvas.height);

const result = await quantizer.quantizeImageData(imageData, {
  maxColors: 32,
  speed: 1,
  dithering: 0.8,
});

// Draw quantized result back to canvas
ctx.putImageData(result.imageData, 0, 0);

quantizer.dispose();

Input Formats

quantizePng accepts multiple input types:

// Uint8Array
const result = await quantizer.quantizePng(pngBytes);

// ArrayBuffer
const result = await quantizer.quantizePng(arrayBuffer);

// Blob
const result = await quantizer.quantizePng(blob);

API Reference

LibImageQuant

Constructor

const quantizer = new LibImageQuant(options?: LibImageQuantOptions);

Option	Type	Default	Description
workerUrl	string	auto-detected	Custom path to the worker module
wasmUrl	string	auto-detected	Custom path to the WASM module directory
initTimeout	number	10000	Worker initialization timeout (ms)
operationTimeout	number	30000	Per-operation timeout (ms)

Methods

quantizePng(pngData, options?)

Quantizes a PNG image from binary data.

• pngData: Uint8Array | ArrayBuffer | Blob - PNG file bytes
• options: QuantizationOptions (optional)
• Returns: Promise<QuantizationResult>

quantizeImageData(imageData, options?)

Quantizes an ImageData object (e.g. from canvas).

• imageData: ImageData - RGBA image data
• options: QuantizationOptions (optional)
• Returns: Promise<QuantizationResult>

dispose()

Terminates the worker, rejects any pending operations, and releases resources. Safe to call multiple times.

QuantizationOptions

{
  speed?: number;          // Speed vs quality (1-10, lower = better quality)
  quality?: {
    min: number;           // Minimum acceptable quality (0-100)
    target: number;        // Target quality (0-100)
  };
  maxColors?: number;      // Maximum colors in palette (2-256)
  dithering?: number;      // Dithering level (0.0-1.0)
  posterization?: number;  // Posterization level (0-4)
}

QuantizationResult

{
  palette: number[][];     // Color palette as [[r,g,b,a], ...]
  pngBytes: Uint8Array;    // Quantized indexed PNG file bytes
  imageData: ImageData;    // Quantized RGBA image data (for canvas)
  quality: number;         // Achieved quality (0.0-1.0)
  paletteLength: number;   // Number of colors in palette
  width: number;           // Image width in pixels
  height: number;          // Image height in pixels
}

Build from Source

Prerequisites

• Rust with the wasm32-unknown-unknown target
• wasm-pack
• Node.js >= 20.19.0
• wasm-opt (optional, for WASM size optimization)

Setup

# Install Rust and wasm-pack
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
curl https://rustwasm.github.io/wasm-pack/installer/init.sh -sSf | sh
rustup target add wasm32-unknown-unknown

# Install dependencies
npm install

# Build
npm run build

Scripts

Script	Description
npm run build	Full build (WASM + TypeScript + types)
npm run build:wasm	Build WASM module only
npm run build:types	Generate TypeScript declarations only
npm run typecheck	Run TypeScript type checking
npm test	Run tests (vitest + browser)
npm run test:watch	Run tests in watch mode
npm run dev	Start Vite dev server
npm run clean	Remove build output

Testing

Tests run in a real browser via Vitest with @vitest/browser and Playwright. No mocks — the actual WASM module is loaded and executed.

# Build first (tests run against built output)
npm run build

# Run tests (headless Chromium)
npm test

The test suite covers:

• High-level API - LibImageQuant class, all input formats, options, disposal, concurrency, error handling
• Low-level WASM - ImageQuantizer, QuantizationResult, PNG encode/decode, memory management
• Result validation - Color accuracy, PNG integrity, transparency roundtrips

Browser Support

Requires WebAssembly and Web Worker support:

• Chrome 57+
• Firefox 52+
• Safari 11+
• Edge 16+

Performance Tips

• Reuse quantizer instances when processing multiple images
• Use appropriate speed settings - higher speed for real-time, lower for final output
• Consider image size - quantization time scales with pixel count
• Call dispose() when done to release the Web Worker

Examples

See examples/test.html for a complete working example with:

• File upload
• Real-time parameter adjustment
• Visual comparison
• Palette display
• Performance metrics

License

MIT License - See LICENSE file for details.

Important Note: This project wraps the libimagequant library, which is dual-licensed under GPL-3.0 and commercial licenses. While this wrapper is MIT licensed, you must ensure you comply with the appropriate libimagequant license for your use case. For commercial use, you may need to obtain a commercial license from the libimagequant authors.

Contributing

• Fork the repository
• Create your feature branch
• Build: npm run build
• Test: npm test
• Submit a pull request

Troubleshooting

Worker Loading Issues

Ensure the worker module is served from the same origin, or pass a custom workerUrl to the constructor.

WASM Loading Issues

• Verify WebAssembly support: typeof WebAssembly === 'object'
• Check browser console for loading errors
• Ensure proper MIME type for .wasm files (application/wasm)
• Pass a custom wasmUrl if the WASM files are hosted separately

Performance Issues

• Large images may take significant time to quantize
• Consider resizing images before quantization
• Use higher speed settings for real-time applications