Neural Network Combined with Fuzzy Logic to Remove Salt and Pepper Noise in Digital Images

2006 ◽  
pp. 23-33 ◽  
Author(s):  
A. Faro ◽  
D. Giordano ◽  
C. Spampinato
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Digital Images ◽  
Salt And Pepper Noise ◽  
Salt And Pepper

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 .

De-noising of images from salt and pepper noise using hybrid filter, fuzzy logic noise detector and genetic optimization algorithm (HFGOA)

2019 ◽  
Vol 79 (5-6) ◽  
pp. 4115-4131 ◽  
Author(s):  
A. Senthil Selvi ◽  
K. Pradeep Mohan Kumar ◽  
S. Dhanasekeran ◽  
P. Uma Maheswari ◽  
S. Ramesh ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Optimization Algorithm ◽  
Genetic Optimization ◽  
Salt And Pepper Noise ◽  
Hybrid Filter ◽  
Salt And Pepper ◽  
Genetic Optimization Algorithm

scholarly journals Modified CPI filter algorithm for removing salt-and-pepper noise in digital images

1996 ◽  
Author(s):  
Nelson H. C. Yung ◽  
Andrew H. S. Lai ◽  
Kim M. Poon
Keyword(s):  
Digital Images ◽  
Salt And Pepper Noise ◽  
Salt And Pepper

scholarly journals High Salt and Pepper Noise Ratio Reduction

2021 ◽  
Vol 10 (9) ◽  
pp. 88-97
Author(s):  
Hatim Zaini ◽  
Ziad Alqadi
Keyword(s):  
Image Processing ◽  
Noise Level ◽  
Digital Images ◽  
Salt And Pepper Noise ◽  
High Noise ◽  
Median Filters ◽  
Negative Effect ◽  
Noise Ratio ◽  
Blurred Images ◽  
Salt And Pepper

Colored digital images are affected by salt and pepper noise, affecting their clarity, contents and properties. The negative effect on the image increases with the increase in the noise level. Filters based on average and median filters are not able to remove SAPN with high noise ratios, and accordingly, blurred images are obtained that cannot be dealt with in various image processing operations. In this paper research a modification will be add to median and average filters making them capable of reducing the noise even it has a high noise ratio, the modified average and median filters will be implanted and some comparisons with other popular filters will be made to show the enhancement of the modified filters.

scholarly journals An Efficient Adaptive Denoising Algorithm for Remote Sensing Images

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Xiujie Qu ◽  
Fu Zhang ◽  
Huan Jia
Keyword(s):  
Remote Sensing ◽  
Digital Images ◽  
Working Environment ◽  
Salt And Pepper Noise ◽  
Remote Sensing Images ◽  
Median Filters ◽  
Almost All ◽  
Salt And Pepper ◽  
Filter Algorithms ◽  
Adaptive Denoising

Typically, after the capturing, imaging, and transferring processes have been accomplished, the digital images will contain a variety of noise, caused by both the equipment itself and by the complex working environment. Consequently, it is necessary to perform a de-noising process to facilitate the extraction of useful information. This paper presents a fast and efficient denoising algorithm, which combines the advantages of traditional median filters and weighted filter algorithms. In this algorithm, the noise in the figure is determined, and those results are applied to adaptively change the size of the window, while assigning different weights to the pixels in the filter window. The experimental results show that we can significantly remove almost all salt and pepper noise, while retaining full image textures, edges, and other minutiae.

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