Lossy image compression using singular value decomposition and wavelet difference reduction

Authors:
Awwal Mohammed Rufai;Gholamreza Anbarjafari;Hasan Demirel
Affiliations:
Department of Electrical Electronics Engineering, Cyprus International University, Lefkoşa, via Mersin 10, North Cyprus, Turkey;IMS Lab, Institute of Technology, University of Tartu, Tartu 50411, Estonia;Department of Electrical Electronics Engineering, Eastern Mediterranean University, Gazimağusa, via Mersin 10, North Cyprus, Turkey
Venue:
Digital Signal Processing
Year:
2014

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Abstract

This paper presents a new lossy image compression technique which uses singular value decomposition (SVD) and wavelet difference reduction (WDR). These two techniques are combined in order for the SVD compression to boost the performance of the WDR compression. SVD compression offers very high image quality but low compression ratios; on the other hand, WDR compression offers high compression. In the Proposed technique, an input image is first compressed using SVD and then compressed again using WDR. The WDR technique is further used to obtain the required compression ratio of the overall system. The proposed image compression technique was tested on several test images and the result compared with those of WDR and JPEG2000. The quantitative and visual results are showing the superiority of the proposed compression technique over the aforementioned compression techniques. The PSNR at compression ratio of 80:1 for Goldhill is 33.37 dB for the proposed technique which is 5.68 dB and 5.65 dB higher than JPEG2000 and WDR techniques respectively.