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Journal of Applied Mathematics
Volume 2014 (2014), Article ID 362716, 7 pages
http://dx.doi.org/10.1155/2014/362716
Research Article

A New Method of Image Denoising for Underground Coal Mine Based on the Visual Characteristics

1School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221008, China
2School of Information and Electronic Engineering, Xuzhou Institute of Technology, Xuzhou, Jiangsu 221008, China

Received 15 January 2014; Accepted 12 March 2014; Published 6 April 2014

Academic Editor: Feng Gao

Copyright © 2014 Gang Hua and Daihong Jiang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Affected by special underground circumstances of coal mine, the image clarity of most images captured in the mine is not very high, and a large amount of image noise is mingled with the images, which brings further downhole images processing many difficulties. Traditional image denoising method easily leads to blurred images, and the denoising effect is not very satisfactory. Aimed at the image characteristics of low image illumination and large amount of noise and based on the characteristics of color detail blindness and simultaneous contrast of human visual perception, this paper proposes a new method for image denoising based on visual characteristics. The method uses CIELab uniform color space to dynamically and adaptively decide the filter weights, thereby reducing the damage to the image contour edges and other details, so that the denoised image can have a higher clarity. Experimental results show that this method has a brilliant denoising effect and can significantly improve the subjective and objective picture quality of downhole images.