Inter-scale correlation and threshold combination denoising model of nonsubsampled contourlet

Xujing Guo; Zulin Wang

doi:10.1117/12.748378

14 November 2007 Interscale correlation and threshold combination denoising model of nonsubsampled contourlet

Xujing Guo, Zulin Wang

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 679046 (2007) https://doi.org/10.1117/12.748378
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Correlation denoising could distinguish noisy and signal coefficients by the correlation degree and thus retain more right edge. But there is a strict requirement to unerring locations. The nonsubsampled contourlet (NSCT) is a shift-invariant directional multiresolution image representation and overcomes the disadvantage of wavelet, the nonoptimal basis for one-dimensional singularity. For the shift-invariance, it could not only preserve more edge details than contourlet but also satisfy the above requirement of correlation denosing. Thus, to combine threshold denoising, we present a novel inter-scale correlation and threshold combination denosing model of NSCT (ISCTC-NSCT). The simulation results have shown that the performance of the above method is superior both in signal to noise ratio (SNR) and edge preservation.

Citation Download Citation

Xujing Guo and Zulin Wang "Interscale correlation and threshold combination denoising model of nonsubsampled contourlet", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679046 (14 November 2007); https://doi.org/10.1117/12.748378

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