CLC number: TN919.8
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2009-12-08
Cited: 6
Clicked: 10697
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.
@article{title="Image compression based on spatial redundancy removal and image inpainting",
author="Vahid BASTANI, Mohammad Sadegh HELFROUSH, Keyvan KASIRI",
journal="Journal of Zhejiang University Science C",
volume="11",
number="2",
pages="92-100",
year="2010",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C0910182"
}
%0 Journal Article
%T Image compression based on spatial redundancy removal and image inpainting
%A Vahid BASTANI
%A Mohammad Sadegh HELFROUSH
%A Keyvan KASIRI
%J Journal of Zhejiang University SCIENCE C
%V 11
%N 2
%P 92-100
%@ 1869-1951
%D 2010
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C0910182
TY - JOUR
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
IS - 2
SP - 92
EP - 100
%@ 1869-1951
Y1 - 2010
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C0910182
Abstract: 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.
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