基于压缩感知的红外与可见光图像融合

Abstract

A novel method to fuse infrared and visible images was proposed based on compressive sensing theory.The method combined Contourlet Transform(CT)with Wavelet Transform(WT)to increase the sparsity of transformed coefficients and also to improve sample patterns and fusion rules.Firstly,the original images were decomposed in a Contourlet domain,and orthogonal wavelet transform was applied to the high level decomposed coefficients.Then,the composite double radially sampling mode with different sampling rates in each decomposition level was used to perform the linear measurements of coefficients and to fuse the measurement values using different rules in eachlevel.Finally,the fused image was reconstructed by using nonlinear conjugate-gradient solution.The experimental results demonstrate that the detail information of fusion image by proposed method is more salient than that of discrete wavelet transform fusion image when sampling rate is 0.5.As compared with WTCS method,the mutual information,spatial frequency and the visual information fidelity of fused image from proposed method are increased by 10%.