2D image compression technique-A survey

Advanced imaging requires storage of large quantities of digitized data. Due to the constrained bandwidth and storage capacity, images must be compressed before transmission and storage. However the compression will reduce the image fidelity, especially when the images are compressed at lower bitrates. The reconstructed images suffer from blocking artifacts and the image quality will be severely degraded under the circumstance of high compression ratios. Medical imaging poses the great challenge of having compression algorithms that reduce the loss of fidelity as much as possible so as not to contribute to diagnostic errors and yet have high compression rates for reduced storage and transmission time. To meet this challenge several hybrid compression schemes have been developed in the field of image processing. This paper presents overview of various compression techniques based on DCT, DWT, ROI and Neural Networks for two dimensional (2D) images.