<title>Spectral image compression for data communications</title>

Abstract

We report a technique for spectral image compression to be used in the field of data communications. The spectral domain of the images is represented by a low-dimensional component image set, which is used to obtain an efficient compression of the high-dimensional spectral data. The component images are compressed using a similar technique as the JPEG- and MPEG-type compressions use to subsample the chrominance channels. The spectral compression is based on Principal Component Analysis (PCA) combined with color image transmission coding technique of 'chromatic channel subsampling' of the component images. The component images are subsampled using 4:2:2, 4:2:0, and 4:1:1-based compressions. In addition, we extended the test for larger block sizes and larger number of component images than in the original JPEG- and MPEG-standards. Totally 50 natural spectral images were used as test material in our experiments. Several error measures of the compression are reported. The same compressions are done using Independent Component Analysis and the results are compared with PCA. These methods give a good compression ratio while keeping visual quality of color still good. Quantitative comparisons between the original and reconstructed spectral images are presented.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.