Compression of Multispectral Images with Comparatively Few Bands Using Posttransform Tucker Decomposition

Up to now, data compression for the multispectral charge-coupled device (CCD) images with comparatively few bands (MSCFBs) is done independently on each multispectral channel. This compression codec is called a monospectral compressor. The monospectral compressor does not have a removing spectral redundancy stage. To fill this gap, we propose an efficient compression approach for MSCFBs. In our approach, the one dimensional discrete cosine transform (1D-DCT) is performed on spectral dimension to exploit the spectral information, and the posttransform (PT) in 2D-DWT domain is performed on each spectral band to exploit the spatial information. A deep coupling approach between the PT and Tucker decomposition (TD) is proposed to remove residual spectral redundancy between bands and residual spatial redundancy of each band. Experimental results on multispectral CCD camera data set show that the proposed compression algorithm can obtain a better compression performance and significantly outperforms the traditional compression algorithm-based TD in 2D-DWT and 3D-DCT domain.