Proceedings ArticleDOI
A Two-Pass Filter for Impulse Noise Reduction Based on Edge Characteristics
Chao-Yu Chen,Chao-Ho Chen,Yi-Li Kuo,Chin-Hsing Chen +3 more
- pp 5-8
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TLDR
Experimental results show that the proposed two-pass filter is more effective for impulse noise reduction to improve image quality; especially the corruption ratio above 20%.Abstract:
In this paper, a two-pass filter is proposed for removing impulse noise to improve image quality. Due to the fact that the edge is more obvious and detected easily, such characteristics of different edges are used to judge whether the pixel is on an edge. Then, the pixels are not on the edges will be filtered by median filter, and further, the other pixels will be detected to preserve original information and reduce impulse noise. Experimental results show that the proposed method is more effective for impulse noise reduction to improve image quality; especially the corruption ratio above 20%.read more
Citations
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Proceedings Article
Iterative average filtering for image denoising
TL;DR: A new nonlinear iterative average filtering technique for removing random impulse noise from images is presented and offers especially good results for strongly corrupted images (corruption pixel ratio above 40%).
Proceedings ArticleDOI
Digital filter for real-time impulse noise suppression in video processing using Dynamic Partial Reconfiguration technique
TL;DR: A hardware implementation of the median filter using Dynamic Partial Reconfiguration (DPR) technique to restore grayscale and color image having salt & peppers and random-valued impulse noise is proposed.
Dissertation
Image Restoration using Soft Computing
TL;DR: Major focus of this thesis has been to study existing modern soft computing based techniques and to develop new image restoration techniques using soft computing to be more generic and useful.
Journal ArticleDOI
Adaptively Directed Image Restoration Using Resilient Backpropagation Neural Network
TL;DR: Zhang et al. as discussed by the authors proposed an adaptive directed denoising filter (ADD filter) based on a neural network, which consists of three major stages: training, filtering, and enhancing.
References
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Journal ArticleDOI
Center weighted median filters and their applications to image enhancement
Sung-Jea Ko,Yong Hoon Lee +1 more
TL;DR: The center weighted median (CWM) filter as discussed by the authors is a weighted median filter that gives more weight only to the central value of each window, which can preserve image details while suppressing additive white and/or impulsive-type noise.
Journal ArticleDOI
A new impulse detector for switching median filters
Shuqun Zhang,Mohammad A. Karim +1 more
TL;DR: A new impulse noise detection technique for switching median filters is presented, which is based on the minimum absolute value of four convolutions obtained using one-dimensional Laplacian operators, and is directed toward improved line preservation.
Journal ArticleDOI
Space variant median filters for the restoration of impulse noise corrupted images
Tao Chen,Hong Ren Wu +1 more
TL;DR: In this article, a generalized framework of median based switching schemes, called multi-state median (MSM) filter, is proposed by using a simple thresholding logic, the output of the MSM filter is adaptively switched among those of a group of center weighted median (CWM) filters with different center weights.
Journal ArticleDOI
Selective removal of impulse noise based on homogeneity level information
TL;DR: A decision-based, signal-adaptive median filtering algorithm for removal of impulse noise, which achieves accurate noise detection and high SNR measures without smearing the fine details and edges in the image.
Journal ArticleDOI
Theoretical analysis of the max/Median filter
Gonzalo R. Arce,M. McLoughlin +1 more
TL;DR: It is shown that threshold decomposition holds for this class of filters, making the deterministic analysis simpler, and this multidimensional filter based on a combination of one-dimensional median estimates is introduced.