Abstract：Multispectral imaging has been widely used in the field of remote sensing. The storage and transmission of large volumes of multispectral data have become significant concerns. Therefore efficient compression is required for storage and transmission. This paper proposes a new multispectral image data compression algorithm （KLT/WT3DSPECK）. First, a 2D wavelet transform is applied to reduce the spatial redundancies. Next a Karhunen-Loeve Transform （KLT） is used to remove the correlation between adjacent spectral bands. Finally a modified 3DSPECK method is proposed and is used to code the transformed coefficients. According to the distribution of energy of the transformed coefficients, a novel 3D octave partitioning scheme and an improved set partitioning zeroblock method are presented. To accelerate the speed and optimize the rate-distortion performance of the embedded bit stream, a fast algorithm of the optimal zeroblock sorting is given. Numerical experiments on two sample multispectral images show that the proposed KLT/WT-3DSPECK algorithm outperforms either the KLT/WT-3DSPIHT algorithm or the 3DWT-based AT-3DSPIHT and 3DSPECK algorithms. Besides having high performance, the KLT/WT-3DSPECK algorithm support progressive transmission.
2005, Vol. 27 
