1 March 2007 Semi-automatic region of interest identification algorithm using wavelets
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Typically, the region of interest (ROI), in the JPEG2000 standard, is manually defined, and then wavelets are used to compress the ROI at a higher bitrate than the rest of the image. The wavelet decomposition in JPEG2000 also lends itself to texture and edge extraction for segmentation and classification purposes. In this paper, a semi-automatic ROI generation algorithm for images is presented, where the texture and edge information provided by the first level of the wavelet decomposition is used to segment the wavelet coefficients. This first-level decomposition provides enough edge and texture information for image segmentation, allowing computational savings. A mask that outlines the ROI is determined based on the entropy calculation of the segmented regions. The advantage of this method is that the segmentation process is entirely performed in the wavelet and not in the pixel domain, therefore offering additional computational efficiency. The resulting ROI is coded using the MAXSHIFT method. The algorithm was applied and successfully demonstrated in several images.
© (2007) Society of Photo-Optical Instrumentation Engineers (SPIE)
Sedig Salem Agili, Sedig Salem Agili, Vittal Balasubramanian, Vittal Balasubramanian, Aldo W. Morales, Aldo W. Morales, } "Semi-automatic region of interest identification algorithm using wavelets," Optical Engineering 46(3), 035003 (1 March 2007). https://doi.org/10.1117/1.2713377 . Submission:

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