Blockwise transform image coding, enhancement and edge detection
Abstract
The goal of this thesis is high quality image coding, enhancement and edge detection. A unified approach using novel fast transforms is developed to achieve all three objectives. Requirements are low bit rate, low complexity of implementation and parallel processing. The last requirement is achieved by processing the image in small blocks such that all blocks can be processed simultaneously. This is similar to biological vision. A major issue is to minimize the resulting block effects. This is done by using proper transforms and possibly an overlap-save technique. The bit rate in image coding is minimized by developing new results in optimal adaptive multistage transform coding. Newly developed fast trigonometric transforms are also utilized and compared for transform coding, image enhancement and edge detection. Both image enhancement and edge detection involve generalized bandpass filtering with fast transforms. The algorithms have been developed with special attention to the properties of biological vision systems.
Degree
Ph.D.
Advisors
Ersoy, Purdue University.
Subject Area
Electrical engineering|Computer science
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