Zero-order entropy in estimating bit allocation for eigenimages in PCA/wavelet compression of spectral images

Zero-order entropy has been applied as a basic scheme to the bit allocation among the eigenimages after the PCA transform in the lossy compression of spectral images. In this study, we enhance this allocation scheme by a nonlinear model. The exponentiation in the model is derived from optimization. The compression/reconstruction process is unsymmetric, the compression using optimization is time-consuming, hut the reconstruction is fast. The new model proved useful and it produced from 0.5 dB to 9 dB better quality compared to the original zero-order entropy allocation with test images from three different imaging systems.