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|Title:||Highly - compacted DCT coefficients||Authors:||Dagher, Issam||Affiliations:||Department of Computer Engineering||Keywords:||Discrete Cosine Transform (DCT)
|Subjects:||Image compression||Issue Date:||2010||Part of:||Journal of signal image and video processing||Volume:||4||Issue:||3||Start page:||303||End page:||307||Abstract:||
In this paper highly-compacted DCT coefficients (HDCT) are presented. This compactness is achieved by sorting in ascending order the data first, then by applying the Discrete Cosine transform (DCT) to the ordered data. Images are highly correlated. DCT exhibits excellent energy compaction. It will be shown that HDCT has much better energy compactness than the DCT. This has the effect of representing every ordered image with very small number of HDCT coefficients (dimensionality reduction). The compression capabilities of the HDCT are presented. HDCT is also applied to face recognition problem. Simulation results on different databases showed high average success rate of this algorithm compared to other algorithms.
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/2069||Ezproxy URL:||Link to full text||Type:||Journal Article|
|Appears in Collections:||Department of Computer Engineering|
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