Lossy image compression using Singular Value Decomposition
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Updated
May 14, 2019 - Python
Lossy image compression using Singular Value Decomposition
DCT-based lossy image compression codec (similar to a JPEG codec)
CAE-ADMM: Implicit Bitrate Optimization via ADMM-Based Pruning in Compressive Autoencoders
image compression simulation using EVD(Eigen Value Decomposition)
Compressive Autoencoder.
CharLS Tools, a set of command line tools to CharLS JPEG-LS library
Playing with lossy image compression based on the singular value decomposition
Authors' PyTorch implementation of "Lossy Image Compression with Quantized Hierarchical VAEs"
A MATLAB implementation of JPEG 2000 Part 1 and Part 15 (HTJ2K) that complies with the conformance testing defined in JPEG 2000 Part 4. The goal of MatHTJ2K is to help a person who wants to develop an HTJ2K-based image compression system to understand the algorithms defined in HTJ2K.
An experimental image codec based on linear factor decomposition
Some algorithms for lossy compression of images
Crystal bindings for Grok
Authors' PyTorch implementation of lossy image compression methods that are based on hierarchical VAEs
Open-source implementation of JPEG2000 Part-15 (or JPH or HTJ2K)
World's Leading Open Source JPEG 2000 Codec
📦 Minecraft: Java Edition resource and data pack optimizer which aims to achieve the best possible compression, performance and protection, improving pack distribution, storage and in-game load times.
JPEG XL image format reference implementation
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