JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
Computerized detection of breast masses in digitized mammograms
Computers in Biology and Medicine
Computer Vision and Image Understanding
Image compression: Maxshift ROI encoding options in JPEG2000
Computer Vision and Image Understanding
High performance scalable image compression with EBCOT
IEEE Transactions on Image Processing
A reversible data hiding method by histogram shifting in high quality medical images
Journal of Systems and Software
Evaluation of Region-of-Interest coders using perceptual image quality assessments
Journal of Visual Communication and Image Representation
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Medical images have high spatial and high bit-depth resolution (12 bits per sample or more). These high resolutions allow computer-aided diagnosis, which are exploited by radiologists to identify relevant medical areas, known as Regions of Interest (ROI). In image compression, ROI coding allows to recover the ROI earlier than the rest of the image. In JPEG2000, ROI coding may be provided through two different mechanisms: either by modifying wavelet coefficients, or by rate-distortion optimization techniques. The former obtains an excellent accuracy to delimit ROIs, but, in some cases, the ROI and the background can not be encoded losslessly; the latter is usually not able to achieve the intended fine-grain accuracy, but it overcomes the lossless encoding shortcoming. This article introduces a ROI coding method based on ratedistortion optimization techniques that recovers the ROI and the background losslessly, regardless of the high bit-depth resolution, and that yields an accuracy equivalent to MaxShift and Scaling, the two compliant JPEG2000 ROI coding methods based on modifying wavelet coefficients. The proposed method is JPEG2000 compliant.