Adaptive Four-dot Median Filter for Removing 1-99% Densities of Salt-and-Pepper Noise in Images

2018 ◽  
Vol 11 (3) ◽  
pp. 47-61 ◽  
Author(s):  
Xin-Ming Zhang ◽  
Qiang Kang ◽  
Jin-Feng Cheng ◽  
Xia Wang
Keyword(s):  
Image Restoration ◽  
Performance Improvement ◽  
Adaptive Filtering ◽  
Median Filter ◽  
Window Size ◽  
Salt And Pepper Noise ◽  
Noise Detection ◽  
Median Filters ◽  
Simple Logic ◽  
Salt And Pepper

In order to accelerate denoising and improve the denoising performance of the current median filters, an Adaptive Four-dot Median Filter (AFMF) for image restoration is proposed in this article. AFMF is not only very efficient and fast in logic execution, but also it can restore the corrupted images with 1–99% densities of salt-and-pepper noise to the satisfactory ones. Without any complicated operation for noise detection, it intuitively and simply distinguishes impulse noises, while keeping the noise-free pixels intact. Only the uncorrupted pixels of the four-dot mask in adaptive filtering windows are used for the adoption of candidates for median finding, whatever filtering window size is. Furthermore, the adoption of recursive median filters leads to denoising performance improvement and faster filtering. The simple logic of the proposed algorithm obtains significant milestones on the fidelity of a restored image. Relevant experimental results on subjective visualization and objective digital measure validate the robustness of the proposed filter.

Reduction of Noise in Restoration of Images Using Mean and Median Filtering Techniques

2021 ◽  
Vol 9 (9) ◽  
pp. 301-313
Author(s):  
Vimal Chauhan
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Median Filter ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Digital Cameras ◽  
Salt And Pepper Noise ◽  
Satellite Imaging ◽  
Mean Filter ◽  
Salt And Pepper

Abstract: The purpose of this paper is to present a study of digital technology approaches to image restoration. This process of image restoration is crucial in many areas such as satellite imaging, astronomical image & medical imaging where degraded images need to be repaired Personal images captured by various digital cameras can easily be manipulated by a variety of dedicated image processing algorithms [2]. Image restoration can be described as an important part of image processing technique. Image restoration has proved to be an active field of research in the present days. The basic objective is to enhance the quality of an image by removing defects and make it look pleasing [2]. In this paper, an image restoration algorithm based on the mean and median calculation of a pixel has been implemented. We focused on a certain iterative process to carry out restoration. The algorithm has been tested on different images with different percentage of salt and pepper noise. The improved PSNR and MSE values has been obtained. Keywords: De-Noising, Image Filtering, Mean Filter & Median Filter, Salt and Pepper Noise, Denoising Techniques, Image Restoration.

Salt-and-pepper noise detection and reduction using fuzzy switching median filter

2008 ◽  
Vol 54 (4) ◽  
pp. 1956-1961 ◽  
Author(s):  
Kenny Toh ◽  
Haidi Ibrahim ◽  
Muhammad Mahyuddin
Keyword(s):  
Median Filter ◽  
Salt And Pepper Noise ◽  
Noise Detection ◽  
Switching Median Filter ◽  
Salt And Pepper

Salt and Pepper Noise Removal Based on GA-BP Algorithm

2011 ◽  
Vol 301-303 ◽  
pp. 1243-1248
Author(s):  
Yin Mao Song ◽  
Xiao Juan Li
Keyword(s):  
Noise Removal ◽  
Bp Algorithm ◽  
Salt And Pepper Noise ◽  
Noise Detection ◽  
Edge Preserving ◽  
Bp Network ◽  
Median Filters ◽  
Noise Filter ◽  
Noise Density ◽  
Salt And Pepper

Noise detection-based median filters have been widely adopted to reduce salt and pepper noise in images. However, since noise pixel is not detected accurately, it is likely to blur the fringe of image under the high noise density. In this paper, we propose an algorithm of salt and pepper noise filter which is based on GA-BP algorithm noise detector to remove the salt and pepper noise in images. The algorithm firstly detect the location of noise pixels by using optimized GA-BP network,then,it introduce edge-preserving function and PRP algorithm to solve the objective function of extreme value further to realize the image denoising. Compared with the traditional algorithms, experimental results show that the proposed algorithm has an evident improvement, and have good characters of generalization, robust and self-adaptive.

An Improved Method of Adaptive Median Filter Based on Noise Density

2014 ◽  
Vol 530-531 ◽  
pp. 403-406 ◽  
Author(s):  
Ping He ◽  
Hong Jian Zhang ◽  
Chao Liu ◽  
Yuan Guo
Keyword(s):  
Euclidean Distance ◽  
Median Filter ◽  
Weighted Average ◽  
Window Size ◽  
Salt And Pepper Noise ◽  
Improved Method ◽  
Adaptive Median Filter ◽  
Noise Density ◽  
Distance Weighted ◽  
Salt And Pepper

To filter salt and pepper noise and protect the texture details of images effectively, an improved method of adaptive median filter is proposed. It can detect the suspicious noise by adjusting the filter window size and adopting the filter algorithm of adaptive texture direction in low density noise area and the filter algorithm of euclidean distance weighted average in high density noise area. Experimental results show that this method has better de-noising and detail-preserving performance.

Enhancing the Performance of One Dimensional Median Filter

2019 ◽  
Vol 118 (7) ◽  
pp. 73-76
Author(s):  
Sharanabasappa ◽  
P Ravibabu
Keyword(s):  
Impulse Noise ◽  
Rank Order ◽  
Median Filter ◽  
Filter Method ◽  
Salt And Pepper Noise ◽  
Edge Preservation ◽  
Word Level ◽  
Look Ahead ◽  
Filter Architecture ◽  
Salt And Pepper

Nowadays, during the process of Image acquisition and transmission, image information data can be corrupted by impulse noise. That noise is classified as salt and pepper noise and random impulse noise depending on the noise values. A median filter is widely used digital nonlinear filter  in edge preservation, removing of impulse noise and smoothing of signals. Median filter is the widely used to remove salt and pepper noise than rank order filter, morphological filter, and unsharp masking filter. The median filter replaces a sample with the middle value among all the samples present inside the sample window. A median filter will be of two types depending on the number of samples processed at the same cycle i.e, bit level architecture and word level architecture.. In this paper, Carry Look-ahead Adder median filter method will be introduced to improve the hardware resources used in median filter architecture for 5 window and 9 window for 8 bit and 16 bit median filter architecture.

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