CCSDS 123.0-B-1 algorithm is an adaptive lossless compression standard for multispectral and hyperspectral images proposed by the Consultative for Space Data Systems. In order to solve the problems existing in CCSDS 123.0-B-1 algorithm, such as the under-utilization of pixel position information and spectral correlation, and the compression rate to be improved, an RMPR (Reduction of Mapped Prediction Residual) algorithm is proposed to optimize the predictor of the algorithm. The RMPR algorithm can adaptively select the prediction points according to the specific position of the current pixel, remove the spectral correlation of hyperspectral images with bidirectional linear prediction, and use the optimized residual mapper to improve the prediction accuracy and shorten the compression code length. Test on ten hyperspectral images shows that the RMPR algorithm significantly outperforms the original algorithm in terms of compression performance, under the premise of lossless compression and no signi- ficant difference in compression efficiency.