Image compression based on Region of Interest (ROI) has been one of the hot topics of interest in image processing. There is not a single widely accepted method for detecting the ROI automatically form an image. To reduce the transmission bandwidth and storage space requirements of gray scale images, an algorithm is suggested for detecting the ROI automatically based on Tsallis entropy method.
Tsallis entropy method is used to segment the image into two segments, the ROI and the background. These two segments can then be compressed at different rates, to avoid losing information in the ROI while achieving a good compression. Different approaches of compression based on wavelets and use of various compression methods are also discussed.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-7028 |
| Date | 01 January 2015 |
| Creators | Budihal Prasad, Adhokshaja Achar |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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