A comprehensive survey on impulse and Gaussian denoising filters for digital images

An adaptive decision based kriging interpolation algorithm for the removal of high density salt and pepper noise in images

A decision based asymmetrically trimmed Winsorized median for the removal of salt and pepper noise in images and videos is proposed. The proposed filter initially classifies the pixels as noisy and non noisy and later replaces the noisy pixels with asymmetrically trimmed modified winsorized median leaving the non noisy pixels unaltered. Exhaustive experiments were conducted on standard image database and the performance of the proposed filter was evaluated in terms of both quantitative and qualitatively with existing algorithm. It was found that the proposed algorithm was found to exhibit excellent noise suppression capabilities by preserving the fine information of the image even at higher noise densities. The performance of the proposed filter was found good even for videos.

A decision based asymmetrically trimmed modified winsorized median filter for the removal of salt and pepper noise in images and videos

This paper introduces a robust edge detection method that relies on an integrated process for denoising images in the presence of high impulse noise. This process is shown to be resilient to impulse (or salt and pepper) noise even under high intensity levels. The proposed switching adaptive median and fixed weighted mean filter (SAMFWMF) is shown to yield optimal edge detection and edge detail preservation, an outcome we validate through high correlation, structural similarity index, and peak signal-to-noise ratio measures. For comparative purposes, a comprehensive analysis of other denoising filters is provided based on these various validation metrics. The non-maximum suppression method and new edge following maximum-sequence are the two techniques used to track the edges and overcome edge discontinuities and noisy pixels, especially in the presence of high-intensity noise levels. After applying predefined thresholds to the grayscale image, and thus obtaining a binary image, several morphological operations are used to remove the unwanted edges and noisy pixels and perform edge thinning to ultimately provide the desired edge connectivity, which results in an optimal edge detection method. The obtained results are compared with other existing state-of-the-art denoising filters and other edge detection methods in support of our assertion that the proposed method is resilient to impulse noise even under high-intensity levels.

A Robust Edge Detection Approach in the Presence of High Impulse Noise Intensity Through Switching Adaptive Median and Fixed Weighted Mean Filtering

The major benefit of a disclosed low-hardware-complexity pipelined rank filter is reduction in hardware complexity and increase in processing speed, due to identical pipelined stages and the absence of mask bits. Field-programmable-gate-array realization of this filter significantly reduces the number of used logic elements and registers, in comparison with the best prior art methods, and, at the same time, increases the maximum operating frequency. One rank-sample result is available at the output on each clock cycle, thus enabling real-time nonlinear image processing.

Low Hardware Complexity Pipelined Rank Filter

In this paper, an efficient non-linear cascade filter for the removal of high density salt and pepper noise in image and video is proposed. The proposed method consists of two stages to enhance the filtering. The first stage is the Decision based Median Filter (DMF) which is used to identify pixels likely to be contaminated by salt and pepper noise and replaces them by the median value. The second stage is the Unsymmetric Trimmed Filter, either Mean Filter (UTMF) or Midpoint Filter (UTMP) which is used to trim the noisy pixels in an unsymmetric manner and processes with the remaining pixels The basic idea is that, though the level of denoising in the first stage is lesser at high noise densities, the second stage helps to increase the noise suppression. Hence, the proposed cascaded filter, as a whole is very suitable for low, medium as well as high noise densities even above 90%. The existing non-linear filters such as Standard Median Filter (SMF), Adaptive Median Filter (AMF), Weighted Median Filter (WMF), Recursive Weighted Median Filter (RWM) performs well only for low and medium noise densities. The recently proposed Decision Based Algorithm (DBA) shows better results upto 70% noise density and at high noise densities, the restored image quality is poor. The proposed algorithm shows better image and video quality in terms of visual appearance and quantitative measures.

http://ieeexplore.ieee.org/iel5/5191366/5204362/05204476.pdf

S. Kalishwaran

Papers

An efficient non-linear cascade filtering algorithm for removal of high density salt and pepper noise in image and video sequence