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胡春海, 张湃, 张海峰. 可实现图像自修复的压缩感知超分辨率成像[J]. 计算机辅助设计与图形学学报, 2012, 24(12): 1621-1630.
引用本文: 胡春海, 张湃, 张海峰. 可实现图像自修复的压缩感知超分辨率成像[J]. 计算机辅助设计与图形学学报, 2012, 24(12): 1621-1630.
Hu Chunhai, Zhang Pai, Zhang Haifeng. Compressed Sensing Super Resolution Imaging with Image Self-restoration[J]. Journal of Computer-Aided Design & Computer Graphics, 2012, 24(12): 1621-1630.
Citation: Hu Chunhai, Zhang Pai, Zhang Haifeng. Compressed Sensing Super Resolution Imaging with Image Self-restoration[J]. Journal of Computer-Aided Design & Computer Graphics, 2012, 24(12): 1621-1630.

可实现图像自修复的压缩感知超分辨率成像

Compressed Sensing Super Resolution Imaging with Image Self-restoration

  • 摘要: 为了在不增加系统复杂度的前提下实现对降质图像的传输、修复及超分辨率成像,基于压缩感知理论和图像的退化模型建立了一个新型的压缩感知系统.该系统利用图像退化模型中降采样操作和模糊算子改进测量矩阵,并提出了基于小波-Shearlet的图像变换作为稀疏表示方法,在重构端结合迭代硬阈值算法重建图像.实验结果表明,文中系统在重构图像的质量和运算效率上均具备一定优势.

     

    Abstract: In order to achieve image transmission,restoration,and super resolution imaging without increasing the system complexity,a new compressed sensing system is designed based on the theory of compressed sensing and image degenerate model.This system modifies the measurement matrix by using the down-sampling operator and blurring operator of the image degenerate model as well as constructs a wavelet-Shearlet based image transform,then combines with the iterative hard threshold algorithm to reconstruct images.Experimental results demonstrate the effectiveness of our system in the quality of the reconstructed images and computing efficiency.

     

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