Compression of the mammography images using quadtree based energy and pattern blocks

Medical images, like any other digital data, require compression in order to reduce disk space needed for storage and time needed for transmission. This thesis offers , a novel image compression method based on generation of the so-called classified energy and pattern blocks (CEPB) is introduced and evaluation results are presented. The CEPB is constructed using the training images and then located at both the transmitter and receiver sides of the communication system. Then the energy and pattern blocks of input images to be reconstructed are determined by the same way in the construction of the CEPB. This process is also associated with a matching procedure to determine the index numbers of the classified energy and pattern blocks in the CEPB which best represents (matches) the energy and pattern blocks of the input images. Encoding parameters are block scaling coefficient and index numbers of energy and pattern blocks determined for each block of the input images. These parameters are sent from the transmitter part to the receiver part and the classified energy and pattern blocks associated with the index numbers are pulled from the CEPB. Moreover, in the second part of our method we used Quadtree too. By this way, all CEPB from quadtree results determined for each block of the input images too. input image is reconstructed block by block in the receiver part using a mathematical model that is proposed by 2 different method: • Reconstruct Based on one block size • Reconstruct Based on Quadtree Evaluation results show that the method provides considerable image compression ratios and image quality even at low bit rates. Test result have shown that Compression ratio and PSNR results is acceptable, moreover, Quadtree method gives better results that fix based block size.