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CLC number: TN919.8

On-line Access: 2010-01-01

Received: 2009-04-02

Revision Accepted: 2009-06-19

Crosschecked: 2009-12-08

Cited: 6

Clicked: 5730

Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.2 P.92-100


Image compression based on spatial redundancy removal and image inpainting

Author(s):  Vahid BASTANI, Mohammad Sadegh HELFROUSH, Keyvan KASIRI

Affiliation(s):  Department of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz, Iran

Corresponding email(s):   ms_helfroush@sutech.ac.ir

Key Words:  Edge extraction, Image compression, Image inpainting, Spatial redundancy

Vahid BASTANI, Mohammad Sadegh HELFROUSH, Keyvan KASIRI. Image compression based on spatial redundancy removal and image inpainting[J]. Journal of Zhejiang University Science C, 2010, 11(2): 92-100.

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journal="Journal of Zhejiang University Science C",
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%T Image compression based on spatial redundancy removal and image inpainting
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%A Keyvan KASIRI
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T1 - Image compression based on spatial redundancy removal and image inpainting
A1 - Vahid BASTANI
A1 - Mohammad Sadegh HELFROUSH
A1 - Keyvan KASIRI
J0 - Journal of Zhejiang University Science C
VL - 11
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SP - 92
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C0910182

We present an algorithm for image compression based on an image inpainting method. First the image regions that can be accurately recovered are located. Then, to reduce the data, information of such regions is removed. The remaining data besides essential details for recovering the removed regions are encoded to produce output data. At the decoder, an inpainting method is applied to retrieve removed regions using information extracted at the encoder. The image inpainting technique utilizes partial differential equations (PDEs) for recovering information. It is designed to achieve high performance in terms of image compression criteria. This algorithm was examined for various images. A high compression ratio of 1:40 was achieved at an acceptable quality. Experimental results showed attainable visible quality improvement at a high compression ratio compared with JPEG.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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