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21. 发明授权

US07224845B1 Bijection mapping for compression/denoising of multi-frame images 有权
标题翻译：用于多帧图像的压缩/去噪的双偏移映射
公开(公告)号：US07224845B1
公开(公告)日：2007-05-29
申请号：US10376491
申请日：2003-02-28
申请人： Leonard E. Russo , Jose L. Paredes , Gonzalo R. Arce
发明人： Leonard E. Russo , Jose L. Paredes , Gonzalo R. Arce
IPC分类号： G06K9/46 , G06K9/00
CPC分类号： G06K9/0063 , H04N19/102 , H04N19/134 , H04N19/14 , H04N19/189 , H04N19/647 , H04N19/90
摘要： A new approach to multispectral image compression where the intra- and cross-band correlations are jointly exploited in a surprisingly simple yet very effective manner. The key component of the algorithm is a bijection mapping of the original multispectral image into a virtual 2 dimensional scalar image. By optimally mapping the multispectral image set into a single 2 dimensional array and by subsequently applying a scalar image coding algorithm, the spatial correlation and the spectral correlation of the multispectral data set are jointly exploited. Based on the statistical characteristics of the multispectral data, the bijection mapping can be optimized to minimize the distortion introduced by the compression algorithm. The optimization reduces to the maximization of a function of the second-order statistics of the multispectral data. At high compression rates, the new algorithm outperforms traditional compression algorithms whenever the cross-band correlation is high and it yields comparable performance at low compression rates.
摘要翻译：多光谱图像压缩的新方法，其中内部和跨带相关性以令人惊讶的简单但非常有效的方式共同利用。该算法的关键组成部分是原始多光谱图像到虚拟二维标量图像的双射映射。通过将多光谱图像集合最佳地映射为单个二维阵列，并通过随后应用标量图像编码算法，共同利用多光谱数据集的空间相关性和光谱相关性。基于多光谱数据的统计特征，可以优化双射映射，以最小化压缩算法引入的失真。优化减少到多光谱数据的二阶统计功能的最大化。在高压缩率下，只要交叉带相关性高，新算法就胜过传统的压缩算法，并且在低压缩率下产生可比较的性能。

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