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计算机工程

• 多媒体技术及应用 • 上一篇    下一篇

基于AMP框架的小波域图像压缩重构

李骜1,李一兵2,林云2   

  1. (1.哈尔滨理工大学计算机科学与技术学院,哈尔滨 150080; 2.哈尔滨工程大学信息与通信工程学院,哈尔滨 150001)
  • 收稿日期:2014-09-09 出版日期:2015-08-15 发布日期:2015-08-15
  • 作者简介:李骜(1986-),男,讲师、博士,主研方向:网络多媒体技术,稀疏表示理论;李一兵,教授、博士;林云,讲师、博士。
  • 基金资助:
    国家自然科学基金资助项目(61301095);黑龙江省自然科学基金资助项目(F201345)。

Wavelet Domain Image Compressive Reconstruction Based on AMP Framework

LI Ao 1,LI Yibing 2,LIN Yun 2   

  1. (1.School of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080,China; 2.Institute of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China)
  • Received:2014-09-09 Online:2015-08-15 Published:2015-08-15

摘要: 针对压缩感知中的图像重构问题,基于近似消息传递(AMP)框架,提出一种新的图像压缩重构算法。该算法推导AMP框架在小波域下的系数迭代公式,证明AMP中滤波函数的操作对象是图像的小波系数,通过小波变换提高处理对象的稀疏度,并引入Wiener函数降低标量函数的求 导复杂度。实验结果表明,与基于梯度投影的重构算法和正交匹配追踪算法相比,该算法具有较好的视觉效果和较高的重构精度。

关键词: 图像重构, 压缩感知, 小波变换, 近似消息传递框架, Wiener滤波

Abstract: This paper proposes a novel image compressive reconstruction algorithm based on Approximate Message Passing(AMP).The novel algorithm derives the formulation in wavelet domain under the AMP framework,and proves that the filter function effects are the wavelet coefficients of image.It uses the wavelet transformation to increase the sparsity of processing objects,and incorporates the Wiener function to decrease the computational complexity.Experimental results demonstrate that,compared with the reconstruction algorithm based on gradient projection and the orthogonal matching pursuit algorithm,the proposed method is realized easily and shows some advantage on both of reconstruction accuracy and visualization.

Key words: image reconstruction, compressive sensing, wavelet transformation, Approximate Message Passing(AMP) framework, Wiener filtering

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