scholarly journals Reconstruction of Corrupted Image From Salt And Pepper Noise From Median Filter

2012 ◽  
pp. 4-6
Author(s):  
Vishal Gautam ◽  
Tarun Varma
Keyword(s):  
Median Filter ◽  
Median Filtering ◽  
Salt And Pepper Noise ◽  
Filtering Algorithm ◽  
Noise Density ◽  
Mean Filter ◽  
Salt And Pepper ◽  
Image Details ◽  
Lower Noise ◽  
Better Than

- Inthis paper,we propose an improved median filtering algorithm. Here, we introduced salt and pepper noise for the image corruption and reconstruct original image using different filters i.e. mean, median and improved median filter. The performance of improved median filter is good at lower noise density levels.The mean filter suppresses little noise and gets the worst results.The experimental resultsshow that our improved median filter is better than previousmedian filterfor lower noise density (upto 60%). It removes most of the noises effectively while preserving image details very well.

An Improved Hybrid Median-Mean Filter Algorithm

2014 ◽  
Vol 701-702 ◽  
pp. 288-292
Author(s):  
Fang Jia ◽  
De Cheng Xu ◽  
Xin Fu
Keyword(s):  
Gaussian Noise ◽  
Median Filter ◽  
Experimental Results ◽  
Median Filtering ◽  
Filtering Algorithm ◽  
Mean Filter ◽  
Image Details ◽  
Mean Filtering

In the process of imaging, digitalization and transmission, images are generally contaminated by Gaussian noise and salt & pepper noise, which cannot be eliminated completely at the same time only by Mean filter or Median filter. Aiming at solving this problem, an improved hybrid median-mean filter algorithm based on the Improved Median Filtering (IMF) algorithm is proposed in this paper. The experimental results show that the new algorithm shows better performance than either Median filtering algorithm or Mean filtering algorithm, which can not only get rid of Gaussian noise and salt & pepper noise simultaneously, but also minimize the contradictions between noise erasing and image details protecting effectively.

scholarly journals Ameliorated mean adaptive median filtering algorithm

2019 ◽  
Vol 118 ◽  
pp. 02069
Author(s):  
Hongming Zhang ◽  
Yongping Wang ◽  
Chuang Peng
Keyword(s):  
Median Filter ◽  
Random Noise ◽  
Infrared Image ◽  
Electrical Equipment ◽  
Median Filtering ◽  
Salt And Pepper Noise ◽  
Filtering Algorithm ◽  
Average Value ◽  
Adaptive Median Filter ◽  
Salt And Pepper

Aiming at the problem that the quality of infrared image decreases due to the large amount of random noise in the process of collection and transmission of infrared image of electrical equipment, and the accuracy of automatic detection of electrical equipment decreases, based on the traditional adaptive median filter algorithm, the adaptive median filter is analyzed, which can filter only the salt and pepper noise below 25%. An improved mean adaptive median filtering algorithm is proposed to overcome the shortcomings of wave effect. Firstly, the filtering window is selected according to the decision setting condition, and then it is judged whether the K-mean value near the center point is a noise point, and if so, the window is increased, otherwise the average value is output. Finally, it is judged whether the value of the current pixel point is noise, and if so, the average value is output, otherwise, the current pixel value is output. The experimental results show that the algorithm can effectively filter salt and pepper noise and Gauss noise, while maintaining the image sharpness, and has good filtering performance on PSNR and MSE indicators.

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.

scholarly journals Simulated evaluation of new switching based median filter for suppressing SPN and RVIN

2019 ◽  
Vol 15 (2) ◽  
pp. 688 ◽  
Author(s):  
Vorapoj Patanavijit ◽  
Kornkamol Thakulsukanant
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Impulsive Noise ◽  
Median Filter ◽  
Median Filtering ◽  
Salt And Pepper Noise ◽  
Removal Method ◽  
The Past ◽  
Salt And Pepper ◽  
Objective Indicators

<p>In the past two decades, the SPN (salt and pepper noise) suppressing method is worldwide interested researches on computer vision and image processing hence many SPN suppressing methods have been proposed. In general, the primary goal of SPN removal method is the suppressing of SPN in digital images thereby one of the recent effective and powerful SPN suppressing methods is a new switching-based median filtering (NSMF), which is innovated for suppressing high density SPN. Consequently, this paper thoroughly examines its efficiency and constrain of a new switching-based median filtering when this filter is used for contaminated image, which is synthesized by SPN and RVIN (random-value impulsive noise). In these simulations, six well-known images (Lena, Mobile, Pepper, Pentagon, Girl, Resolution) with two impulsive noise classes (SPN and RVIN) are used for measuring the its efficiency and constrain. An evaluation of the efficiency is conducted with many previous methods in forms of subjective and objective indicators.</p>

scholarly journals Recognition of Pole Piece Defects of Lithium Battery Based on Sparse Decomposition

2015 ◽  
Vol 9 (1) ◽  
pp. 540-546
Author(s):  
Gong Chen ◽  
Xilu Lou ◽  
Chunxiang Li ◽  
Xifang Zhu ◽  
Xu Cheng ◽  
...  
Keyword(s):  
Background Noise ◽  
Lithium Battery ◽  
Multiplicative Noise ◽  
Median Filter ◽  
Salt And Pepper Noise ◽  
Sparse Decomposition ◽  
Additive And Multiplicative Noise ◽  
Salt And Pepper ◽  
Noise Experiment ◽  
Better Than

To study surface denoising of lithium battery film to extract feature effectively. The best atomic function by sparse decomposition is acquired by iteration under added noise, gaussian noise, salt and pepper noise, additive and multiplicative noise. Terminating iteration value is got by observation and used to filter under specific background noise. Experiment shows sparse decomposition denoising performance is better than the median filter, sparse decomposition is good for detection of lithium battery film defects.

An Image Filtering Algorithm for Removing Mixed Noise

2013 ◽  
Vol 433-435 ◽  
pp. 383-388 ◽  
Author(s):  
Mao Xiang Chu ◽  
An Na Wang ◽  
Rong Fen Gong
Keyword(s):  
Gaussian Noise ◽  
Weighting Function ◽  
Median Filter ◽  
Bilateral Filter ◽  
Salt And Pepper Noise ◽  
Filtering Algorithm ◽  
Noise Simulation ◽  
Mixed Noise ◽  
Local Edge ◽  
Salt And Pepper

In order to remove salt-and-pepper noise and Gaussian noise in image, a novel filtering algorithm is proposed in this paper. The novel algorithm can preserve image edge details as much as possible. Firstly, five-median-binary code (FMBC) is proposed and used to describe local edge type of image. Secondly, median filter algorithm is improved to remove salt-and-pepper noise by using FMBC. Then, local enhanced bilateral filter with FMBC and a new type of exponential weighting function is used to remove Gaussian noise. Simulation results show that the algorithm proposed in this paper is very effective not only in filtering mixed noise but also in preserving edge details.

scholarly journals Probabilistic Decision Based Average Trimmed Filter for the Removal of High-Density Salt and Pepper Noise

2020 ◽  
Vol 8 (5) ◽  
pp. 4350-4357
Keyword(s):  
Signal To Noise Ratio ◽  
Median Filter ◽  
Absolute Error ◽  
Noise Removal ◽  
Low Noise ◽  
Salt And Pepper Noise ◽  
Ratio Image ◽  
Noise Density ◽  
Chest X Ray ◽  
Salt And Pepper

The paper focuses on the evacuation of salt and pepper noise from a contaminated image. A probabilistic decision based average trimmed filter (PDBATF) is proposed for both high and low noise density. The proposed algorithm addresses the issue related to even number of noise-free pixel in trimmed median filter for the calculation of processing pixel. The proposed average trimmed filter is incorporated for low noise density while the proposed patch else average trimmed filter is applied for high noise density. Finally, they are combined together to develop the proposed PDBATF. The proposed algorithm show an excellent noise removal capability compared to the recently developed algorithms in terms of peak signal to noise ratio, image enhancement factor, mean absolute error and execution time. It works very efficiently in de-noising contaminated medical images such as chest-x-ray and malaria-blood-smear.

scholarly journals An Iterative Weighted-Mean Filter for Removal of High-Density Salt-and-Pepper Noise

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1990
Author(s):  
Fengyu Chen ◽  
Minghui Huang ◽  
Zhuxi Ma ◽  
Yibo Li ◽  
Qianbin Huang
Keyword(s):  
Noise Removal ◽  
High Density ◽  
Salt And Pepper Noise ◽  
Weighted Mean ◽  
Real Time Processing ◽  
Noise Density ◽  
Mean Filter ◽  
Execution Speed ◽  
Salt And Pepper

Salt-and-pepper noise, which is often introduced by sharp and sudden disturbances in the image signal, greatly reduces the quality of images. Great progress has been made for the salt-and-pepper noise removal; however, the problem of image blur and distortion still exists, and the efficiency of denoising requires improvement. This paper proposes an iterative weighted-mean filter (IWMF) algorithm in detecting and removing high-density salt-and-pepper noise. Three steps are required to implement this algorithm: First, the noise value and distribution characteristics were used to identify the noise pixels, effectively improving the accuracy of noise detection. Second, a weighted-mean filter was applied to the noisy pixels. We adopted an un-fixed shape symmetrical window with better detail preservation ability. Third, this method was performed iteratively, avoiding the streak effect and artifacts in high noise density. The experimental results showed that IWMF outperformed other state-of-the-art filters at various noise densities, both in subjective visualization and objective digital measures. The extremely fast execution speed of this method is quite suitable for real-time processing.

Adaptive Switching Median Filter Based on GA-BP Neural Network

2013 ◽  
Vol 753-755 ◽  
pp. 2980-2984
Author(s):  
Xiao Ling Ye ◽  
Yan Yan Dou ◽  
Bo Liu
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Digital Images ◽  
Median Filter ◽  
Poor Performance ◽  
Salt And Pepper Noise ◽  
Switching Median Filter ◽  
Image Pixels ◽  
Salt And Pepper ◽  
Image Details

For the poor performance of conventional filtering algorithms in removing salt and pepper noise from digital images under high noise density,an adaptive switching median filter algorithm based on BP neural network optimized by genetic algorithm (GA) is proposed to detect and remove salt and pepper noise from images. Firstly,the initial weights and thresholds of BP neural network are optimized by genetic algorithm.Then image pixels are devided into either signal or noise points by the trained network automatically. The detected noise points will be removed by adaptive switching median filter algorithm,but nothing to do with the signal points. Experiment results show that the proposed algorithm significantly outperforms the others and efficiently removes salt and pepper noise from digital images without distorting image details and textures .

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