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Li, C.B. (2009) An Efficient Al-gorithm For Total Variation Regularization with Applications to the Single Pixel Camera and Compressive Sensing. Master of Arts, Rice University, Houston, Texas.

has been cited by the following article:

• TITLE: Compressed Sensing Based on the Single Layer Wavelet Transform for Image Fusion

  AUTHORS: Guohui Yang, Wude Xu, Bo Zheng, Fanglan Ma, Xuhui Yang, Hongwei Ma, Hongxia Zhang, Genliang Han

  KEYWORDS: Image Fusion, Compressed Sensing, Single Layer Wavelet Transform

  JOURNAL NAME: Journal of Computer and Communications, Vol.4 No.15, November 28, 2016

  ABSTRACT: In this paper, a new method of combination single layer wavelet transform and compressive sensing is proposed for image fusion. In which only measured the high-pass wavelet coefficients of the image but preserved the low-pass wavelet coefficient. Then, fuse the low-pass wavelet coefficients and the measurements of high-pass wavelet coefficient with different schemes. For the reconstruction, by using the minimization of total variation algorithm (TV), high-pass wavelet coefficients could be recovered by the fused measurements. Finally, the fused image could be reconstructed by the inverse wavelet transform. The experiments show the proposed method provides promising fusion performance with a low computational complexity.