Playing with Low-density parity-check codes

Belief propagation with sparse matrices (scipy.sparse) in Python for LDPC codes. Includes NumPy implementation of message passing (min-sum and sum-product) and a few other decoders.

A data packing technique for QC-LDPC codec RTL min-sum layer decoding architecture

AVX implementation of different LDPC decoders MS NMS SCMS SCSP under floor/layer schedulers

An optimized Matlab implementation of Loopy Belief Propagation for stereo matching that focuses on speed. It uses matrix operations and other techniques to make the program run even faster.

Special Project - QCLDPC (2019 Spring)

An optimized (very fast) Matlab implementation of Loopy Belief Propagation for stereo matching. It uses the "Min-Sum" version of the algorithm and the "Accelerated" (Right-Left-Down-Up pass) message update schedule.

LDPC simulation

An optimized (very fast) Matlab implementation of Loopy Belief Propagation for stereo matching. It uses the "Min-Sum" version of the algorithm and the "Synchronous" message update schedule.

Optimized (very fast) stereo matching algorithms in MATLAB. It includes the Block Matching, Dynamic Programming, Semi-Global Matching, Semi-Global Block Matching and Belief Propagation algorithms.

A C++ implementation of Loopy Belief Propagation for image denoising. It uses the "min-sum" variation of the algorithm and the "Accelerated" (Right-Left-Down-Up pass) message update schedule.

A C++ implementation of Loopy Belief Propagation for stereo matching. It uses the "min-sum" variation of the algorithm and the "Accelerated" (Right-Left-Down-Up pass) message update schedule.

A C++ implementation of Loopy Belief Propagation for stereo matching that offers the choice between six message update schedules. It uses the "Min-Sum" version of the algorithm with a small improvement for better results.

A Matlab implementation of Loopy Belief Propagation for stereo matching. It includes the "Sum-Product", "Max-Product" and "Min-Sum" versions of the algorithm.

🖼️ Implement fast stereo matching algorithms in MATLAB, including Block Matching and Dynamic Programming, to generate accurate disparity maps for stereo images.