高频频带再分解在遥感图像压缩中的应用
Application of High-Frequency Redecomposition to Remote Sensing Image Compression
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摘要: 针对以人工目标为主的遥感图像特点,提出一种基于高频频带再分解的压缩方法.首先,采用对称-反对称多小波对图像进行分解,在迭代分解LL频带的同时水平分解LH频带、垂直分解HL频带,在复杂度变化不大的前提下提高了频率分辨率;然后,采用SPIHT算法压缩频域图像,使某一子带系数与下一层相应的子带系数构成父子关系,从而更好地利用了带间相关性.实验结果证实了该算法压缩遥感图像的有效性.Abstract: This paper proposes a new image compression scheme based on high-frequency bands redecompression according to the characteristics of remote sensing images which contain man-made objects. By the scheme, the image is decomposed at first using a symmetric-antisymmetric multiwavelets. LH subband and HL subband are decomposed in horizontal, vertical direction individually while LL subband is decomposed iteratively. This decomposition approach achieves better high-frequency distinguishability without increasing computational complexity too much. Then, SPIHT is used to compress transformed coefficients. Each coefficient at a given subband is related to a set of coefficients at the next finer subband to create parent-children relationship and it is a better method exploiting interscale dependencies. Experimental result confirms the efficiency of the new scheme to remote sensing image.
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