Image compression based on spatial redundancy removal and image inpainting

Vahid BASTANI; Sadegh HELFROUSH; Keyvan KASIRI

doi:10.1631/jzus.C0910182

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Image compression based on spatial redundancy removal and image inpainting

图像处理 | Updated：2022-08-31

- Image compression based on spatial redundancy removal and image inpainting
- Image compression based on spatial redundancy removal and image inpainting
- 信息与电子工程前沿（英文） 2010年11卷第2期页码：92-100
- Affiliations：
  
  Department of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz, Iran
- Author bio：
  
  ‡Corresponding Author
- Funds：
- DOI：10.1631/jzus.C0910182
  中图分类号：
- 收稿：2009-04-02，
  
  修回：2009-12-08，
  
  录用：2009-06-19，
  
  纸质出版：2010-02
- Accepted：
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Image compression based on spatial redundancy removal and image inpainting[J]. 信息与电子工程前沿（英文）, 2010,11(2):92-100.

Vahid BASTANI, Sadegh HELFROUSH, Keyvan KASIRI. Image compression based on spatial redundancy removal and image inpainting[J]. Frontiers of Information Technology & Electronic Engineering, 2010, 11(2): 92-100.
Image compression based on spatial redundancy removal and image inpainting[J]. 信息与电子工程前沿（英文）, 2010,11(2):92-100. DOI： 10.1631/jzus.C0910182.

Vahid BASTANI, Sadegh HELFROUSH, Keyvan KASIRI. Image compression based on spatial redundancy removal and image inpainting[J]. Frontiers of Information Technology & Electronic Engineering, 2010, 11(2): 92-100. DOI： 10.1631/jzus.C0910182.

摘要

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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