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Proceedings Paper

Infrared image denoising based on stationary wavelet transform
Author(s): Zhihong Xiao; Jiale Shi; Zongqi Guan
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Paper Abstract

Firstly, infrared image is decomposited using stationary wavelet transform, it is proposed based on stationary wavelet transform with Interscale and Intrascale Dependencies for infrared image denoising. Then the minimum mean square-error estimation is applyed to estimated coefficient. The wavelet coefficients are revised using the correlations between coefficients at the same scale. The denoised image is obtained through inverse wavalet transform. The experimental results show the infrared image can be denoised better than the method neglecting the correlations between Intrascales and have a well SNR as well as the visual quality.

Paper Details

Date Published: 26 February 2010
PDF: 7 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75463B (26 February 2010); doi: 10.1117/12.853569
Show Author Affiliations
Zhihong Xiao, Zhejiang Wanli Univ. (China)
Jiale Shi, Zhejiang Wanli Univ. (China)
Zongqi Guan, Zhejiang Wanli Univ. (China)


Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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