ENHANCEMENT AND COMPRESSION TECHNIQUES FOR HYPERSPECTRAL DATA

The next generation of satellite-borne sensors will combine high spati al resolution with fine spectral resolution. A typical data set for a single frame of imagery may contain a few hundred images occupying man y gigabytes of space. Clearly, traditional image processing algorithms cannot be directly applied to such a vast quantity of data. We invest igate enhancement and compression algorithms that use the spectral cor relation present in high-resolution imagery to reduce the computationa l complexity of processing the imagery. The algorithm employs a princi pal component transformation to reduce the size of the data set. Enhan cing the reduced set of images provides equivalent results to processi ng each of the original images with far fewer computations. The compre ssion algorithm utilizes a hybrid discrete cosine transform-differenti al pulse code modulation (DCT-DPCM) transform. The DCT is computed for each image, a bit map is generated for the DCT coefficients, and DPCM is used to encode the coefficients across the bands. Compression at l ess than 0.5 bits/pixel with negligible visual degradation is obtained .