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.

scholarly journals A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression

2014 ◽  
Vol 2014 ◽  
pp. 1-15
Author(s):  
Hilario Gómez-Moreno ◽  
Pedro Gil-Jiménez ◽  
Sergio Lafuente-Arroyo ◽  
Roberto López-Sastre ◽  
Saturnino Maldonado-Bascón
Keyword(s):  
Support Vector Machines ◽  
Noise Reduction ◽  
Digital Images ◽  
State Of The Art ◽  
Noise Removal ◽  
Support Vector ◽  
Salt And Pepper Noise ◽  
Vector Machines ◽  
Classification And Regression ◽  
Salt And Pepper

We present a new impulse noise removal technique based on Support Vector Machines (SVM). Both classification and regression were used to reduce the “salt and pepper” noise found in digital images. Classification enables identification of noisy pixels, while regression provides a means to determine reconstruction values. The training vectors necessary for the SVM were generated synthetically in order to maintain control over quality and complexity. A modified median filter based on a previous noise detection stage and a regression-based filter are presented and compared to other well-known state-of-the-art noise reduction algorithms. The results show that the filters proposed achieved good results, outperforming other state-of-the-art algorithms for low and medium noise ratios, and were comparable for very highly corrupted images.

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