Applications of medical images are increasing rapidly, moreover the
medical images produced by the imaging devices occupies more volume of space.
Medical information system needs to store huge amount of data in the form of
medical images for future record and also these images are required to be transmitted
over network to the place of specialist to obtain diagnostics opinion. Because of the
limited availability of space and bandwidth, an efficient compression technique is
needed to reduce the bits to store and transmit these images. In this paper, we propose
an efficient scheme of medical image compression based on region of interest using
Peano space filling curve. In this method, region containing the most useful
diagnostic features are treated as region of interest (ROI), pixels in ROI region are
arranged using Peano space filling curve (PSFC) and entropy encoded without any loss in quality. The
remaining regions are treated as non region of interest(NROI) and are encoded with singular value
decomposition followed by entropy encoding. The encoded ROI and NROI region are combined to give
the compressed output. The performance of the proposed compression technique with various encoding
such as Huffman and LZW along with Peano Space Filling curve reordering is compared with standard
JPEG2000 compression. The result shows that proposed method gives better performance in terms of
PSNR and Compression Ratio.
Keywords: Region of interest, peano space filling curve, LZW, PSNR, CR.
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