MRI image compression using level set method and biorthogonal CDF wavelet based on lifting scheme
Imane Haouam, Mohammed Beladgham, Bendjillali Ridha Ilyas, Habchi yassine · 2018
image compression optimizes the performance of any digital system by reducing time and cost. interested parties In medical diagnostics field provide more information about the image with a precision and completeness of diagnosis which related to a good quality, so the main objective of compression is to research an optimal reduction of image size without losing the quality. In this article, we proposed a medical image compression algorithm that combines geometric active contour model and biorthogonal wavelet transform. In this method it is necessary to localize the region of interest, using the level set for an optimal reduction, then we use the lifting scheme biorthogonal CDF (biorthogonal lifting scheme CDF9/7, Gall 5/3 and FB), coupled with the set partitioning in hierarchical trees algorithm., the proposed algorithm is superior to traditional methods for MRI images. The level set and CDF9/7 LIFTING scheme algorithm coupled with SPIHT provides very important PSNR (Peak Signal to Noise Ration) and MSSIM (Mean Structural Similarity) values.