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�������պ����ѧѧ�� 2005, Vol. 31 Issue (02) :197-201    DOI:
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Remote sensing image compression based on visual model and image feature
Jiao Runhai, Li Yuancheng, Hou Jingbiao*
School of Computer Science and Technology, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

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Abstract�� With characteristics of complicated texture and rich edges, remote sensing image is usually hard to achieve high compression ratio. Energy distribution among wavelet subbands at different orientations and scales was statisticed, then an adaptive quantization method for different wavelet subbands coefficients was proposed, in the method contrast sensitivity function(CSF) of human vision system(HVS) and energy distribution characteristic were both considered. The quantization method was applied to an existing embedded wavelet image coder and the compression results show that comparing with method without psychovisual quantization, this method gets better visual quality under the same compression ratio (only with little peak signal noise ratio(PSNR) degradation).
Keywords�� image compression   remote sensing image   wavelet transform   human vision system   quantization     
Received 2004-06-20;
Fund:

����863����������Ŀ(2004AA783041); �����������л���������Ŀ

About author: ����(1977-),��,����������,��ʿ��, runhaijiao@sina.com.
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����, ��Ԫ��, ���.�����Ӿ�ģ�ͺ�ͼ��������ң��ͼ��ѹ��[J]  �������պ����ѧѧ��, 2005,V31(02): 197-201
Jiao Runhai, Li Yuancheng, Hou Jingbiao.Remote sensing image compression based on visual model and image feature[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2005,V31(02): 197-201
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http://bhxb.buaa.edu.cn//CN/     ��     http://bhxb.buaa.edu.cn//CN/Y2005/V31/I02/197
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