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中国科学院大学学报 ›› 2009, Vol. 26 ›› Issue (2): 235-242.DOI: 10.7523/j.issn.2095-6134.2009.2.013

• 论文 • 上一篇    下一篇

基于边缘和梯度场的图像表示和压缩方法

葛仕明, 程义民, 李杰, 潘浩   

  1. 中国科学技术大学电子科学与技术系, 肥 230027
  • 收稿日期:2008-03-21 修回日期:2008-04-18 发布日期:2009-03-15
  • 通讯作者: 葛仕明

Image representation and compression using edge and gradient field

GE Shi-Ming, CHENG Yi-Min, LI Jie, PAN Hao   

  1. Department of Electronic Science and Technology, University of Science and Technology of China, Hefei 230027, China
  • Received:2008-03-21 Revised:2008-04-18 Published:2009-03-15

摘要:

提出一种基于边缘和梯度场的图像表示和压缩方法.将图像表示成边缘域的像素和非边缘域的梯度场,并分别进行编码.编码端,采用自适应四叉树分解和一维小波变换编码边缘域,采用二维小波变换编码梯度场.解码端,由对逆变换得到的边缘域和梯度场,通过梯度域变分重构进行解码恢复.方法能用于无损和有损图像压缩,具有较好的压缩性能,并能有效地克服边缘附近的振铃效应.

关键词: 图像表示, 图像压缩, 梯度域重构, 小波变换, 四叉树, Bandelet变换

Abstract:

This paper presents a novel image representation and compression framework using edge and gradient fields. The original image was represented with the pixels in edge region and the gradient fields in non-edge region, and they were encoded separately. At the encoder side, the edge region map was encoded using an adaptive quadtree decomposition and 1D wavelet transform, and the gradient fields were encoded using standard 2D wavelet coder. At the decoder side, a gradient domain variation reconstruction method was utilized to restore the decoded image from the resulting edge region and gradient fields after inverse transform. The proposed framework can provide both lossless and lossy image compression in high compression rate, and can avoid the so-called ring phenomena near edges effectively.

Key words: image representation, image compression, gradient domain reconstruction, wavelet transform, quadtree, Bandelet transform

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