nQuantCpp includes top 6 color quantization algorithms for visual c++ producing high quality optimized images.
-
Updated
Oct 15, 2026 - C++
nQuantCpp includes top 6 color quantization algorithms for visual c++ producing high quality optimized images.
Experiments with structure-aware, error diffusion dithering algorithms, and other ways to improve beyond Floyd-Steinberg.
DitherMe creates Watch Dogs 2 DedSec-style dithered images and GIFs, replicating the iconic glitchy hacker aesthetic
Fast pairwise nearest neighbor based algorithm with C# console
Fast pairwise nearest neighbor based algorithm with javascript
nQuantGpp includes top 10 color quantization algorithms for g++ producing high quality optimized images.
Fast pairwise nearest neighbor based algorithm with Java Swing
Dither Go: A fast and the most correct image dithering library for Python
Dither images and video with 24 algorithms, 11 palettes and a stackable effects pipeline. Browser app, desktop builds and a TypeScript library.
Fast pairwise nearest neighbor based algorithm with android
Coursework for EE569 (Digital Image Processing) at USC for the Spring 2021 Semester
Pixelates image the old-fashioned way.
Agent skill (SKILL.md) that maximizes document quality and readability over fax — converts a PDF to a 1-bit CCITT-G4 PDF/TIFF that arrives LEGIBLE after Group-3 transmission, with 17 halftone methods and a multi-up comparison preview. For Claude and OpenAI Codex.
Generate halftone stego images and extract payloads from them.
Android app for pick and crop an image and apply - FloydSteinberg - Error Diffusion algorithm
Dithering for E Ink Spectra 6 panels that models dot gain, compared side by side with the paperlesspaper app's dithering.
Palette-structure-aware error diffusion dithering in Oklab: dither against a small, designer-chosen palette and keep the error where the eye cannot see it.
Dithering with Pascal Cellular Automata as probabilistic rules
My homework submissions for the digital image processing class @ USC
Conversão de imagens para tons binários preservando a percepção visual através de difusão de erro. Inclui exemplos em RGB e grayscale com Pillow, NumPy e Matplotlib.
To associate your repository with the error-diffusion topic, visit your repo's landing page and select "manage topics."