Many classes of images contains spatial regions which are more important than other regions. Compression methods which are capable of delivering higher reconstruction quality are attractive in this situation for the i...
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Many classes of images contains spatial regions which are more important than other regions. Compression methods which are capable of delivering higher reconstruction quality are attractive in this situation for the important parts. For the medical images, only a small portion of the image might be diagnostically useful, but the cost of a wrong interpretation is high. Hence, regionbasedcoding (RBC) technique is significant for medical image compression and transmission. Lossless compression in these 'regions' and lossy compression for rest of image can helps to achieve high efficiency and performance in telemedicine applications. This paper proposes an automated, efficient and low complexity, lossless, scalable RBC for Digital Imaging and Communications in Medicine (DICOM) images. The advantages of RBC are exploited in this paper, segmenting the region into various regions of importance and subjecting varying bit-rates for optimal performance. Moreover, the combined effects of Integer Wavelet Transform (IWT) and bit-rate limiting compression technique for lesser important regions helps reconstruct the image, reversibly, up to a desired quality. The overall compression thus reaches a satisfactory level to be able to safely transmit the image in limited bandwidth over a telemedicine network and reconstruct diagnostic details for treatment, most faithfully.
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