Correlation-based Joint Acquisition and Demosaicing of Visible and Near-infrared Images

Zahra Sadeghipoor, Yue M. Lu, and Sabine Süsstrunk

IEEE International Conference on Image Processing, 2011

Abstract

Joint processing of visible (RGB) and near-infrared (NIR) images has recently found some appealing applications, which make joint capturing a pair of visible and NIR images an important problem. In this paper, we propose a new method to design color filter arrays (CFA) and demosaicing matrices for acquiring NIR and visible images using a single sensor. The proposed method modifies the optimum CFA algorithm proposed in [1] by taking advantage of the NIR/visible correlation in the design process. Simulation results show that by applying the proposed method, the quality of demosaiced NIR and visible images is increased by about 1 dB in peak signal-to-noise ratio over the results of the optimum CFA algorithm. It is also shown that better visual quality can be obtained using the proposed algorithm.

[1] Yue M. Lu, Clément Fredembach, Martin Vetterli, and Sabine Süsstrunk, "Designing color filter arrays for the joint capture of visible and near-infrared images," In Proc. of IEEE International Conference on Image Processing, 2009.

Results (on the 25 test images)

In each row from left to right:
1. The original visible image
2. The visible image demosaiced by the optimum CFA algorithm
3. The visible image demosaiced by the proposed algorithm
4. The original NIR image
5. The NIR image demosaiced by the optimum CFA algorithm
6. The NIR image demosaiced by the proposed algorithm
(Click on the images to see the full resolution)

Original visible	Optimum CFA (visible)	Proposed algorithm (visible)	Original NIR	Optimum CFA (NIR)	Proposed algorithm (NIR)