Novel context modeling scheme for lossless image compression using statistical reference

A novel context modeling scheme is presented for loss-less image compression. First, each line in the input image is divided into 1 times N line segments, called processing unit (PU). Then, the statistical reference is evaluated in each PU, which reveals the randomness of pixels in the local image region. The context is designed based on both neighbor pixels and the statistical reference. Finally, each pixel is adaptively compressed based on the proposed context condition. In the experiment, the proposed scheme yields the comparable performance to the standard JPEG-LS , while the number of context conditions are decreased by 30%, Moreover, the compression performance of the proposed system shows slightly better performance than the new image compression standard of JPEG-XR.