Adaptive noise reduction scheme for salt and pepper
Tina Gebreyohannes,Dong-Yoon Kim +1 more
Reads0
Chats0
TLDR
A new adaptive noise reduction scheme for images corrupted by impulse noise that can remove salt and pepper noise with noise density as high as 90% and produce better result in terms of qualitative and quantitative measures of images is presented.Abstract:
In this paper, a new adaptive noise reduction scheme for images corrupted by impulse noise is presented. The proposed scheme efficiently identifies and reduces salt and pepper noise. MAG (Mean Absolute Gradient) is used to identify pixels which are most likely corrupted by salt and pepper noise that are candidates for further median based noise reduction processing. Directional filtering is then applied after noise reduction to achieve a good tradeoff between detail preservation and noise removal. The proposed scheme can remove salt and pepper noise with noise density as high as 90% and produce better result in terms of qualitative and quantitative measures of images.read more
Citations
More filters
Journal ArticleDOI
Median Filter Performance Based on Different Window Sizes for Salt and Pepper Noise Removal in Gray and RGB Images
TL;DR: In this article, the performance of median filter based on the effective median per window by using different window sizes and cascaded median filters was evaluated in MATLAB simulations on a gray and RGB images.
Journal ArticleDOI
Image fusion using pca in cs domain
TL;DR: A new efficient image fusion method for compressed sensing imaging that does not need to recovery process and provides promising fusion performance in both visual comparison and comparison using objective measures is proposed.
Posted Content
Image Denoising Using Interquartile Range Filter with Local Averaging
TL;DR: A novel approach to suppress noise from the image is conducted by applying the interquartile range (IQR) which is one of the statistical methods used to detect outlier effect from a dataset.
Journal Article
Edge detection using sobel method with Median filter
TL;DR: This paper proposes an improved algorithm which used the Sobel operator to detect the edges with median filter to remove the unwanted noise of an image; the results demonstrate this filter is simpler and better performing than average filter and also detects the edges accurately.
References
More filters
Journal ArticleDOI
Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization
TL;DR: This scheme can remove salt-and-pepper-noise with a noise level as high as 90% and show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only.
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
A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises
K.S. Srinivasan,D. Ebenezer +1 more
TL;DR: A new decision-based algorithm is proposed for restoration of images that are highly corrupted by impulse noise that removes the noise effectively even at noise level as high as 90% and preserves the edges without any loss up to 80% of noise level.
Journal ArticleDOI
Order statistics in digital image processing
TL;DR: In this article, a family of nonlinear filters based on order statistics is presented, and the probabilistic and deterministic properties of the best known and most widely used filter, the median filter, are discussed.
Journal ArticleDOI
Noise Adaptive Fuzzy Switching Median Filter for Salt-and-Pepper Noise Reduction
K.K.V. Toh,Nor Ashidi Mat Isa +1 more
TL;DR: A novel two-stage noise adaptive fuzzy switching median (NAFSM) filter for salt-and-pepper noise detection and removal that employs fuzzy reasoning to handle uncertainty present in the extracted local information as introduced by noise.