Simultaneous image fusion and demosaicing via compressive sensing

• The proposed method is performed on raw mosaic images of single-sensor color imaging devices.
• The demosaicing and fusion problem is cast as an ill-posed inverse problem inherently and the fused image is obtained directly.
• The extended joint sparse model is used to exploit the inter-channel correlation of color components of the source images.

In this paper, a compressive sensing based simultaneous fusion and demosaicing method for raw data of single-chip imaging camera is introduced. In order to meet the incoherence constraints of compressive sensing theory, the popular Bayer CFA is replaced with a random panchromatic color filter array. Then, the demosaicing problem is cast as an ill-posed inverse problem inherently and the compressive sensing technology is employed to solve the inverse problem. The restored sparse coefficients of different images are further fused with ℓ1ℓ1-norm of the coefficients being served as activity measurements. The final fused image is reconstructed from the fused sparse coefficients. The extended joint sparse model is further used to exploit the inter-channel correlation of different color components. The simulation results illustrated in Experimental Section demonstrate that the proposed method gives both superior quantitative and qualitative performances.