Abstract :
In this paper, a method for lossless and near lossless compression of large digital mammograms is proposed. This method is based on a predictive coder that uses integer-to-integer operations, and generates a two-layer embedded bit stream (i.e. near-lossless and refinement layer). The maximum tolerated pixel distortion is guaranteed in the near lossless component. Comparisons with other proposed approaches are based on a database of high-resolution 12 bits/pixel digital mammograms. The simulation results indicate that our lossless compression method can offer average bit rates 39, 5%, 24%, 7% and 2.5% better than PNG, JPEG 2000, JPEG-lossless, and LOCO, respectively. Besides, for the same images, the proposed method offers near lossless compression at relatively low computational cost, providing an average bit rate of 2.57 bits/pixel and PSNR of 47.77 dB.
Keywords :
data compression; distortion; image coding; mammography; medical image processing; integer-integer operation; mammographic digital image compression; near lossless component; pixel distortion; predictive coder; two-layer embedded bit stream; Bit rate; Computational efficiency; Computational modeling; Digital images; Image coding; Image databases; PSNR; Pixel; Streaming media; Transform coding; Adaptive coding; Image coding; Linear predictive coding; Mammography;
