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autowhitebalance

efficient and robust white balance algorithm

awesome-color-constancy

Resources for Color Constancy and Illumination Estimation

b64.c

Base64 encode/decode

blindimagequalityassessment

Blind image quality assessment with BRISQUE algorithm as a Windows console application

camera-pipeline-ui

cfacompression

Automatically exported from code.google.com/p/cfacompression

colorconstancy_utils

针对ColorCheckerDatasets的一些工具，包括经典恒常性算法的实现，groundtruth处理结果，以及实现利用网络模型输出进行色片校正的方法。

cs344

Introduction to Parallel Programming class code

cuda-programming

Sample codes for my CUDA programming book

cudahandbook

Source code that accompanies The CUDA Handbook.

efficient-illuminant-estimation-for-color-constancy-using-grey-pixels

exposure-fusion

Exposure Fusion in Matlab

face-detection

本科毕业设计 基于Haar特征与AdaBoost算法的人脸检测的实现

ffcc

Fast Fourier Color Constancy: an auto white balance solution with machine learning in Fourier space

gic

isp pipeline_gic

git_test

for git command practice

homogeneity-based-demosaicing

A simple version of demosaicing algorithms for Bayers filtered images

hybridhdr

A hybrid multiple exposure image fusion approach for HDR image synthesis

imagesharpenning

interactive_wb_correction

Reference code for the paper Interactive White Balancing for Camera-Rendered Images Mahmoud Afifi and Michael S. Brown. In Color and Imaging Conference (CIC), 2020.

kmeans

A CUDA implementation of the k-means clustering algorithm

learning-cmake

learning cmake

mean-shifted-gray-pixel

Matlab Implementation of VISSAP 2019 <<Revisiting Gray Pixel for Statistical Illumination Estimation>>

msrcr-restoration

Retinex Algorithms: C++ source code of SSR, MSR, MSRCR algorithm

openisp

Image Signal Processor

openssl_test

OpenSSL's usage

openvx_tutorial

Khronos OpenVX Tutorial Material

rawtherapee

A powerful cross-platform raw photo processing program

reproducible-image-denoising-state-of-the-art

Collection of popular and reproducible image denoising works.

scenerecognition

Scene recognition using multiple feature extractors (tiny-images, D-SIFT, BoVW, PHoW) and different classifiers (KNN, SVM).