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Compression of multispectral and multi-view images with inverse pyramid decomposition

机译:逆金字塔分解压缩多光谱和多视图图像

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摘要

In this paper, a new approach for compression of multi-view and multispectral images, based on the Inverse Pyramid Decomposition (IPD), is presented. This approach is applicable to large number of spectral images or views of same object, processed as a common group. For this, their histograms are calculated and compared. The image, whose histogram is most similar with these of the remaining ones in the group, is used as a reference. The image decomposition starts with the reference image, which is processed with some kind of orthogonal transform, using limited number of transform coefficients only and after inverse transform is obtained the coarse approximation of the image. The IPD then branches out into several parts, corresponding to number of images in the group. The first approximation used in the group is that, calculated for the reference image. In result is obtained high compression and very good visual quality of the restored images.
机译:在本文中,提出了一种基于逆金字塔分解(IPD)的多视图和多光谱图像压缩新方法。此方法适用于作为共同组处理的大量光谱图像或同一对象的视图。为此,计算并比较其直方图。直方图与组中其余直方图最相似的图像用作参考。图像分解从参考图像开始,该参考图像仅使用有限数量的变换系数进行某种正交变换处理,并且在逆变换之后获得图像的粗略近似。然后,IPD会分成几部分,对应于组中的图像数量。该组中使用的第一近似值是针对参考图像计算的。结果,获得了高压缩率和恢复图像的非常好的视觉质量。

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