Memory efficient lossless compression of image sequences with JPEG-LS and temporal prediction
In this paper, a lossless encoder for image sequences based on JPEG-LS defined for still images with temporal-extended prediction and context modeling is proposed. As embedded systems are one important field of application of the codec, on-line lossy reference frame compression is used to reduce the encoder's memory requirement. Variations of the pixel values in the reference frame due to lossy compression are acceptable since the predictor provides only estimations of the pixel values being encoded in the current frame. Larger variations decrease the final lossless compression performance of the encoder such that a trade-off between the memory requirement and the overall compression ratio is required. Different compression algorithms for the reference frame, including JPEG, JPEG 2000 and near-lossless JPEG-LS, and their impacts on the memory requirement and the overall lossless compression ratio have been studied. Experimental results show 9.6% or more gain in lossless compression ratio compared to applying the standard JPEG-LS frame-by-frame and 80% reduction in the encoder buffer size compared to storing the uncompressed reference frame.