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Salt-And-Pepper Noise Removal
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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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>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Residual Transformer Fusion Network for Salt and Pepper Image Denoising
A deep convolutional neural network for salt-and-pepper noise removal using selective convolutional blocks
A Two-stage Method for Non-extreme Value Salt-and-Pepper Noise Removal
Salt and pepper noise removal method based on stationary Framelet transform with non-convex sparsity regularization
NAMF: A Non-local Adaptive Mean Filter for Salt-and-Pepper Noise Removal
Convolutional Neural Network with Median Layers for Denoising Salt-and-Pepper Contaminations
A Nonlinear Acceleration Method for Iterative Algorithms
A Greedy Approach to $\ell_{0,\infty}$ Based Convolutional Sparse Coding
Dual Reweighted Lp-Norm Minimization for Salt-and-pepper Noise Removal
Noise2Noise: Learning Image Restoration without Clean Data
Markov Random Field Model-Based Salt and Pepper Noise Removal
Image Restoration Using Joint Statistical Modeling in Space-Transform Domain
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.