An image can be decomposed into the structural component and the geometric texturalcomponent.Based on this idea,an efficient two-layered compressing algorithm is proposed,which uses2nd generation bandelets and wavelet...An image can be decomposed into the structural component and the geometric texturalcomponent.Based on this idea,an efficient two-layered compressing algorithm is proposed,which uses2nd generation bandelets and wavelets.First,an original image is decomposed into the structuralcomponent and the textural component,and then these two components are compressed using waveletsand 2nd generation bandelets respectively.Numerical tests show that the proposed method worksbetter than the bandelets and JPEG2000 in some specific SAR scene.展开更多
To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform ...To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.展开更多
文摘An image can be decomposed into the structural component and the geometric texturalcomponent.Based on this idea,an efficient two-layered compressing algorithm is proposed,which uses2nd generation bandelets and wavelets.First,an original image is decomposed into the structuralcomponent and the textural component,and then these two components are compressed using waveletsand 2nd generation bandelets respectively.Numerical tests show that the proposed method worksbetter than the bandelets and JPEG2000 in some specific SAR scene.
基金supported by the National Natural Science Foundation of China(6067309760702062)+3 种基金the National HighTechnology Research and Development Program of China(863 Program)(2008AA01Z1252007AA12Z136)the National ResearchFoundation for the Doctoral Program of Higher Education of China(20060701007)the Program for Cheung Kong Scholarsand Innovative Research Team in University(IRT 0645).
文摘To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.
