Vector quantization and signal compression
Vector quantization and signal compression
Compression of multispectral images by spectral classification and transform coding
IEEE Transactions on Image Processing
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In the paper is presented a new method for compression of multispectral images, based on the Inverse Difference Pyramid decomposition. The method is applicable for any number of multispectral images of same object. The processing is performed as follows. First, the histograms of the multispectral images are calculated and compared. The image, whose histogram is most similar with these of the remaining ones, is chosen to be a reference one. The image decomposition starts with the reference image, which is processed with some kind of orthogonal transform, using a limited number of transform coefficients only. With the so obtained coefficients values is calculated the coarse approximation of the processed image. The IDP decomposition then branches out into several directions, corresponding to the number of multispectral images. The first approximation for all multispectral images is that of the reference image. Each branch is developed individually, using the same approximation. In result of this processing is obtained high compression and very good visual quality of the restored images. This approach gives better results than these, obtained with methods, based on the JPEG and JPEG 2000 standards.