Compressing medical images by morphology filter voting strategy and ringing effect elimination

We describe a novel medical image coder that adopts a hybrid wavelet deringing algorithm. The proposed algorithm uses spectrum reorganization, classification, block similarity, and a deringing filter to encode medical images. The coefficients of each wavelet tree are organized into a wavelet block to reduce image complexity. Following the spatial location of the block-gathering operation, classification and block-similarity are used to further reduce the total bit rate. Meanwhile, quad-tree decomposition and a set of morphological filters for reducing the ringing artifacts is presented. This set of filters employs 8 predefined morphological operations, namely, 4 structuring elements (SEs), each of which includes both a dilation and an erosion operation. The voting strategy is used to select the most suitable morphological filter for each block. Experimental results demonstrate that the proposed technique enhances the quality of the reconstructed image in both the peak SNR (PSNR) and perceptual results compared to JPEG2000 and set partitioning in hierarchical trees (SPIHT) given the same bit rate.