126 skills found · Page 1 of 5
bloc97 / Anime4KA High-Quality Real Time Upscaler for Anime Video
wenbihan / Reproducible Image Denoising State Of The ArtCollection of popular and reproducible image denoising works.
m-tassano / FastdvdnetFastDVDnet: A Very Fast Deep Video Denoising algorithm
mikigal / Anime4K GUIAnime upscaler GUI application based on Anime4K shaders which allows to save upscaled video to disk
jlygit / AI Video EnhanceThis repository collects the state-of-the-art algorithms for video/image enhancement using deep learning (AI) in recent years, including super resolution, compression artifact reduction, deblocking, denoising, image/color enhancement, HDR.
kwsou / Video2xVideo upscaler using popular upscaling algorithm waifu2x to magnify and denoise artifacts from low resolution videos
lbasek / Image Denoising BenchmarkBenchmarking Denoising Algorithms with Real Photographs
j2kun / FftPython code and wav files for the post "The Fast Fourier Transform Algorithm, and Denoising a Sound Clip"
april-org / April AnnAPRIL-ANN toolkit (A Pattern Recognizer In Lua with ANNs). This toolkit incorporates ANN algorithms (as dropout, stacked denoising auto-encoders, convolutional NNs), with other pattern recognition methods as HMMs among others. Additionally, in experimental stage, it is possible to perform automatic differentiation, for advanced ML research.
praveenVnktsh / Non Local MeansPython implementation of the Non Local Means algorithm for image denoising.
zhangprofessor / Fast Non Local Means And Asymptotic Non Local MeansNon-Local means denoising (NLM) algorithm is a milestone algorithm in the field of image processing. The proposal of NLM has opened up the non-local method which has a deep influence. This paper performed a revisit for NLM from two aspects as follows: 1. To alleviate the high computational complexity problem of NLM, a fast algorithm was constructed, which was based on cross-correlation and fast Fourier transform; 2. NLM always blur structures and textures during the noise removal, especially in the case of strong noise. To solve this problem, an Asymptotic Non-Local Means image denoising algorithm is put forward, which uses the property of noise variance to control the filtering parameters. Numerical experiments illustrate that the fast algorithm is 27 times faster than classical implementation with standard parameter configuration, and the ANLM uniformly outperforms classical NLM, in terms of both PSNR and visual effects.
courageface / Wavelet DenoisingSome algorithms of wavelet denoising based on PyWavelets.
aminshabani / BM3DMatlab implementation of BM3D Algorithm for Image denoising.
Xingorno / Optimized Bayesian Nonlocal Means With Block OBNLMOptimized bayesian nonlocal-means algorithm for denoising ultrasound image
gkh178 / Noise Adaptive Switching Non Local MeansAiming at the removal of salt-and-pepper noise, a noise adaptive switching non-local means denoising algorithm (NASNLM) is proposed in this program. For noise detection, the pixels of image are divided into the noise and the non-noise points. For filtering, four different filtering techniques are adopted: switching filtering, noise adaptive median filtering, edge-perserving filtering and non-local means filtering. Switching filtering can keep the gray-value of non-noise points unchanged. Noise adaptive median filtering can suppress the high-density salt-and-pepper noise. Edge-preserving filtering can preserve more image edges and details. Non-local means filtering can further improve the ability of noise suppression and detail maintenance. Experiments demonstrate that for removal of the high-density salt-and-pepper noise by NASNLM algorithm, a better denoising effect is obtained than other methods.
kundajelab / CodaCoda: a convolutional denoising algorithm for genome-wide ChIP-seq data
Om-Doiphode / Image PipelineThe image pipeline takes raw image from sensor and convert it to meaningful image. Several algorithms like debayering, Black Level correction, auto-white balance, denoising.. will be first implemented to construct a meaningful image. Then additional algorithms can be implemented on the constructed image to post-process it. Like Flipping, blending and overlaying images. All algorithms will be implemented on a static raw image captured from a sensor. The first part of this project is similar to what happens in an ISP (Image Signal Processor) in which all algorithms are designed based on hardware, but we will be designing those such that they are hardware independent.
JanSochman / TVdenoisingImplementation of TV denoising algorithms from "A. Chambolle, T. Pock. A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging. Journal of Mathematical Imaging and Vision, 2011"
svvenkatakrishnan / Plug And Play PriorsAn algorithmic framework to experiment with different image priors via denoising algorithms for inverse problems.
Logrus / BM4D GPUBM4D denoising algorithm implementation with CUDA
