Papers with Code 아카이브

Salt-And-Pepper Noise Removal

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 6
보존된 평가 기록: 18

Salt-and-pepper noise is a form of noise sometimes seen on images. It is also known as impulse noise. This noise can be caused by sharp and sudden disturbances in the image signal. It presents itself as sparsely occurring white and black pixels.

<span style="color:grey; opacity: 0.6">( Image credit: NAMF )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AliRafiee7/SeConvNet

공식 코드

A deep convolutional neural network for salt-and-pepper noise removal using selective convolutional blocks

https://github.com/Jahid12012021/Adaptive-Weight-Modified-Riesz-Mean-Filter-For-High-Density-Salt-and-Pepper-Noise-Removal

공식 코드

Adaptive Weight Modified Riesz Mean Filter For High-Density Salt and Pepper Noise Removal

https://github.com/NVlabs/noise2noise

공식 코드

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/ProfHubert/NAMF

공식 코드

NAMF: A Non-local Adaptive Mean Filter for Salt-and-Pepper Noise Removal

https://github.com/llmpass/medianDenoise

공식 코드

Convolutional Neural Network with Median Layers for Denoising Salt-and-Pepper Contaminations

https://github.com/COMP6248-Reproducability-Challenge/selfsupervised-denoising

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/ChungHanYang/Image-retoration-based-on-SRresnet

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/WangChen0902/noise2noise-paddle

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/Wenchao-Du/Neighbor2Neighbor_Pytorch

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/ZhenyuTan/Noise2Noise-Cryo-EM-image-denoising

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/fanbeatsman/tensorflow-quick-start-image-processing-focus-

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/foolish0/n2n

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/harshit0511/Unsupervised-Image-denoising

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/hungyiwu/average-joe

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/ishandutta2007/Image-Denoising-Landscape

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/itsuki8914/simply-noise2noise-TF

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/joeylitalien/noise2noise-pytorch

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/johnPertoft/noise2noise

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/juglab/Noise2Noise-with-CSBDeep

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/leili666/denoise_deep_learning

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/saiteja2901/NVDIA_AI_NoiseRemoval

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/shivamsaboo17/Deep-Restore-PyTorch

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/tgieruc/Noise2Noise_PyTorch

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/vlcekl/n2n-tomo

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/zzskyy0301/ML_PROJECT

Noise2Noise: Learning Image Restoration without Clean Data

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.