An effective lossless compression algorithm for medical image set based on denoise improved MMP method

This paper introduces denoising preprocessing technology, image set redundancy and similarity. Both the min-max differential method and the min-max predictive method, which are used to remove set redundancy, are studied in detail. Then, the deficiency of the MMP method is analyzed and the method for predicting levels in MMP is improved to remove correlation among pixels further. Meanwhile, an effective lossless compression algorithm, denoise improved min-max predictive algorithm (DIMMP), is presented in this paper. It combines denoising preprocessing technology and improved MMP method, and can remove background noise and strong correlation in medical image sets effectively. The experimental results indicate that the compression ratio of DIMMP algorithm is much higher than that of MMD/MMP relative methods, and conventional two-dimensional image compression algorithms. This algorithm is one of ideal compression algorithms for medical image sets at present, and can be widely used in medical image storage systems.