Multispectral data compression using bidirectional interbandprediction

The introduction of high spatial and spectral resolution sensors on-board remote-sensing spacecraft has increased, by orders of magnitude, the data rates which need to be sustained on the down-link or cross-link transmission channels. Since these channels are severely limited in capacity, the need arises to perform on-board compression to reduce the volume of data which would need to be down-linked. This paper discusses the development and refinement of a low complexity lossy spectral/spatial compression method which provides high compression ratios at low levels of distortion. The developed techniques uses pixels in adjacent bands to predict the intensity of pixels in the band being compressed via a simple linear prediction model. This prediction method when combined with a low-distortion discrete cosine transform (DCT) block coding method yields performance comparable to block-adaptive Karhunen-Loeve Transform (KLT)-DCT methods without incurring the complexity penalty of the KLT. The methods' performance suffers under misregistration. A fractional-pixel interpolation enhancement to the basic technique significantly improves the performance in the case of misregistered bands