Optimized Hybrid DCT-SVD Computation over Extremely Large Images

Iwan Setiawan(1), Akbari Indra Basuki(2), Didi Rosiyadi(3),

DOI: https://doi.org/10.15294/jte.v13i2.31879


(1) Research Center for Informatics, BRIN
(2) Research Center for Informatics, BRIN
(3) Research Center for Informatics, BRIN

Abstract

High performance computing (HPC) is required for image processing especially for picture element (pixel) with huge size. To avoid dependence to HPC equipment which is very expensive to be provided, the soft approach has been performed in this work. Actually, both hard and soft methods offer similar goal which are to reach time computation as short as possible. The discrete cosine transformation (DCT) and singular values decomposition (SVD) are conventionally performed to original image by consider it as a single matrix. This will result in computational burden for images with huge pixel. To overcome this problem, the second order matrix has been performed as block matrix to be applied on the original image which delivers the DCT-SVD hybrid formula. Hybrid here means the only required parameter shown in formula is intensity of the original pixel as the DCT and SVD formula has been merged in derivation. Result shows that when using Lena as original image, time computation of the singular values using the hybrid formula is almost two seconds faster than the conventional. Instead of pushing hard to provide the equipment, it is possible to overcome computational problem due to the size simply by using the proposed formula.

Keywords

digital image processing; discrete cosine transformation; huge image computing; singular values decomposition

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