Super-Spatial Structure Prediction Compression of Medical - M. Ferni Ukrit; G.R. Suresh (Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 2016)
The demand to preserve raw image data for further processing has been increased with the hasty growth of digital technology. In medical industry the images are generally in the form of sequences which are much correlated. These images are very important and hence lossless compression Technique is required to reduce the number of bits to store these image sequences and take less time to transmit over the network The proposed compression method combines Super-Spatial Structure Prediction with inter-frame coding that includes Motion Estimation and Motion Compensation to achieve higher compression ratio. Motion Estimation and Motion Compensation is made with the fast block-matching process Inverse Diamond Search method. To enhance the compression ratio we propose a new scheme Bose, Chaudhuri and Hocquenghem (BCH). Results are compared in terms of compression ratio and Bits per pixel to the prior arts. Experimental results of our proposed algorithm for medical image sequences achieve 30% more reduction than the other state-of-the-art lossless image compression methods.