A rate control algorithm for encoding multispectral images from remote sensing satellites

This letter presents a rate allocation algorithm that can be used when the Consultative Committee for Space Data Systems (CCSDS) lossy image compressor is applied to encode multispectral images. This algorithm is a numerical solution to the rate control problem when multiple information sources are compressed independently. Given the rate distortion curves and a total bit rate, the algorithm performs an efficient search to find the best rate distribution among the components that produces the lowest distortion. It is shown that the algorithm introduced here is asymptotically optimal. Furthermore, the relationship between performance and complexity can be easily controlled. The efficiency of the algorithm is tested when CCSDS compressor is used to encode the Karhunen and Loève Transform components of multispectral images. The test is performed for a group of images from different multispectral sensors. The convergence speed and the rate distortion curve are evaluated. Numerical results are compared to the performance of the same compressor when it uses the rate control algorithm based on the Gaussian rate distortion function. It is shown that the proposed algorithm can produce improvements over 2 dB in the Peak Signal-to-Noise Ratio even with a reduced computational complexity.