# icy_sixel
A high-performance, 100% pure Rust implementation of a SIXEL encoder and decoder.
I wanted a pure Rust implementation to simplify deployment of my cross-platform applications.
In version 0.4.0, I rewrote the encoder using [quantette](https://github.com/IanManske/quantette),
a high-quality color quantization library licensed under MIT/Apache-2.0. It uses Wu's algorithm
with Floyd-Steinberg dithering for excellent results.
The decoder is a clean-room implementation based on the SIXEL specification, with SIMD optimizations for maximum performance.
## Features
- **SIXEL Encoder**: High-quality color quantization with quantette (Wu's algorithm + Floyd-Steinberg dithering)
- **SIXEL Decoder**: Clean-room implementation with RGBA output and SSE2 SIMD acceleration
- **Transparency Support**: Full alpha channel handling in both encoder and decoder
- **Pure Rust**: No C dependencies, easy to build and deploy
- **Cross-platform**: Works on Linux, macOS, and Windows
## Installation
Add this to your `Cargo.toml`:
```toml
[dependencies]
icy_sixel = "0.4"
```
## Usage
### Encoding an Image to SIXEL
```rust
use icy_sixel::{sixel_encode, EncodeOptions};
// RGBA image data (4 bytes per pixel)
let rgba = vec![
255, 0, 0, 255, // Red pixel
0, 255, 0, 255, // Green pixel
0, 0, 255, 255, // Blue pixel
];
let options = EncodeOptions::default();
let sixel = sixel_encode(&rgba, 3, 1, &options)?;
print!("{}", sixel);
```
### Encoding with Custom Options
```rust
use icy_sixel::{sixel_encode, EncodeOptions, QuantizeMethod};
let options = EncodeOptions {
max_colors: 64, // Use only 64 colors (2-256)
diffusion: 0.875, // Floyd-Steinberg dithering strength (0.0-1.0)
quantize_method: QuantizeMethod::Wu, // or QuantizeMethod::kmeans()
};
let sixel = sixel_encode(&rgba, width, height, &options)?;
```
### Decoding SIXEL to Image Data
```rust
use icy_sixel::sixel_decode;
let sixel_data = b"\x1bPq#0;2;100;0;0#0~-\x1b\\";
let image = sixel_decode(sixel_data)?;
// image.rgba contains RGBA pixel data (4 bytes per pixel)
// image.width and image.height contain dimensions
```
## CLI Tool
The crate includes a command-line tool for encoding and decoding:
```bash
# Install the CLI
cargo install sixel
# Encode a PNG to SIXEL (outputs to stdout by default)
sixel encode image.png
# Encode with custom settings
sixel encode image.png -o output.six --colors 64 --diffusion 0.5 --method kmeans
# Read from stdin
# Decode SIXEL to PNG
sixel decode image.six -o output.png
# Decode from stdin
## Architecture
### Encoder
The encoder uses [quantette](https://github.com/IanManske/quantette) for high-quality
color quantization with Wu's algorithm and Floyd-Steinberg dithering. This produces
excellent results, especially for images with gradients or complex color distributions.
### Decoder
The decoder is a clean-room implementation derived from the SIXEL specification:
- Returns RGBA buffers (4 bytes per pixel) for easy integration with graphics libraries
- SIMD-accelerated horizontal span filling on x86/x86_64 (SSE2)
- Optimized with color caching and loop unrolling
- Comprehensive bounds checking prevents buffer overflows
## Showcase
Original image for reference (596×936 pixels, 879 KB PNG):

### Color Palette Comparison (Wu quantizer, full diffusion)
| 256 | 1.1 MB |  |
| 16 | 440 KB |  |
| 2 | 105 KB |  |
### Dithering Comparison (Wu quantizer, 16 colors)
| Off (0.0) | 420 KB |  |
| Full (0.875) | 440 KB |  |
### Quantizer Comparison (256 colors, full diffusion)
| Wu | 1.1 MB |  |
| K-means | 1.3 MB |  |
## Benchmarks
Performance measurements on the test image (596×936 pixels, beelitz_heilstätten.png):
### Encoder Performance
| Default (Wu, 256 colors, full diffusion) | 41.7 ms |
#### Quantizer Comparison
| Wu | 41.8 ms | Fast, default |
| K-means | 88.1 ms | 2.1× slower |
#### Color Count Impact
| 256 | 42.0 ms |
| 16 | 16.3 ms |
| 2 | 10.8 ms |
#### Diffusion Strength Impact
| Off (0.0) | 21.3 ms |
| Low (0.3) | 31.7 ms |
| Medium (0.5) | 34.1 ms |
| Full (0.875) | 41.9 ms |
### Decoder Performance
| Simple SIXEL | 151 ns |
| Complex SIXEL | 677 ns |
| Repeated patterns | 1.46 µs |
#### Scaling with Size
| 10 | 1.3 µs |
| 50 | 15.9 µs |
| 100 | 52.6 µs |
| 200 | 209 µs |
#### Color Palette Size
| 1 | 150 ns |
| 4 | 485 ns |
| 16 | 2.0 µs |
| 64 | 12.4 µs |
*Benchmarks run with `cargo bench` using Criterion on Linux.*
## License
Licensed under the Apache License, Version 2.0 — see [LICENSE](LICENSE) for details.