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Bag, Rajib
- Detection and Removal of High Density Random Valued Impulse Noise
Authors
1 Department of Computer Science and Engineering, Supreme Knowledge Foundation Group of Institutions, Mankundu, Hooghly, IN
2 Department of Computer Science and Engineering, Supreme Knowledge Foundation Group of Institutions, Mankundu, Hooghly, IN
3 Department of Computer Science and Engineering, Netaji Subhash Engineering College, Techno City Garia, Kolkata, IN
Source
Digital Image Processing, Vol 7, No 8 (2015), Pagination: 242-246Abstract
In this paper, it has been intended to detect the random valued noise and then remove it with the approximation of neighboring pixels. The detection process comprises of two parts. One for the border detection and other for the detection of the rest of the image. In detection process median is computed taking fixed 5×5 window. A pre-defined threshold value is set for the detection of corrupted and un-corrupted pixels. In removal process row wise and column wise matrix operations are separately performed on two distinct images. The output of the above two operations are merged together to get a new matrix. Then conditional mean operation is performed to replace the noisy pixels. Lastly border removal is done and the overall image is further smoothed by unconditional mean operation. Experimental result shows that the proposed filter outperform other filters in respect of performance at noise density as high as 65%.
Keywords
Random Valued Impulse Noise, Mean Filter, Row Wise Operation, Column Wise Operation, Merging, PSNR.- Neighborhood Based Pixel Approximation for High Level Salt and Pepper Noise Removal
Authors
1 Dept. of CSE, Narula Institute of Technology, Agarpara, Kolkata-109, WB, IN
2 Dept. of CSE, SKFGI, Mankundu, Hooghly- 712139, WB, IN
3 Netaji Subhash Engineering College (under West Bengal University of Technology), Technocity, Garia, Panchpota, Kolkata-152,WB, IN
Source
Digital Image Processing, Vol 6, No 8 (2014), Pagination: 346-351Abstract
Digital gray scale images contain salt and pepper noise often due to capturing difficulties. Removal of such impulsive noise is commonly taken care by median based filters. These median based filters are inefficient when the noise level is particularly very high. This paper presents a de-noising technique where noisy pixel’s value is approximated by neighborhood pixels. This technique is expected to work in such high noise levels. Experimental results with this proposed technique show that proposed method provide better performance with respect to both Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and Image Enhancement Factor (IEF). The developed filter also performs acceptably well even at a noise level as high as 90%.