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

Abstract

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.