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.