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

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  • Gang Hua
  • Daihong Jiang

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.

Suggested Citation

  • Gang Hua & Daihong Jiang, 2014. "A New Method of Image Denoising for Underground Coal Mine Based on the Visual Characteristics," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-7, April.
  • Handle: RePEc:hin:jnljam:362716
    DOI: 10.1155/2014/362716
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