Detail-preserving median based filters in image processing
Pattern Recognition Letters
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Inpainting and Zooming Using Sparse Representations
The Computer Journal
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
Adaptive median filters: new algorithms and results
IEEE Transactions on Image Processing
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This paper proposes a novel two-stage denoising method for removing random-valued impulse noise from an image. First, a modified adaptive center-weighted median filter (MACWMF) is used to detect the pixels which are likely to be corrupted by the impulse noise (called the noise candidates). Then the noise candidates are reconstructed by using the image inpainting method in an iterative manner until convergence. The proposed method leads to a simple and very effective denoising algorithm for the random-valued impulse noise removal. It is experimentally shown that the proposed algorithm outperforms the state-of-the-art denoising techniques for the removal of random-valued impulse noise both visually and quantitatively.