Detail-preserving median based filters in image processing
Pattern Recognition Letters
Fast noise variance estimation
Computer Vision and Image Understanding
Communications of the ACM
EURASIP Journal on Applied Signal Processing
IEEE Transactions on Fuzzy Systems
Tri-state median filter for image denoising
IEEE Transactions on Image Processing
Noise adaptive soft-switching median filter
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Selective removal of impulse noise based on homogeneity level information
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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All kinds of median filters have been often adopted in impulse noise reduction. However, many details (e.g., thin lines and step edges) are easily lost, especially at high noise situation. Although many new techniques were added to these filters, the results of image filtering are still not satisfactory. Thus, in this paper, a cost function-based filter is proposed. The corrupted pixels are processed by differentiating the cost function. During image processing, values of the uncorrupted pixels are required to be transformed into constant terms of the cost function, thus, a difference-type noise detector is presented in this paper. During simulations, the proposed filter is compared with several filters in the numerical value and the vision, respectively. Experimental results show that the proposed filter can very effectively remove impulse noise and preserve more details of original images.