21 February 2014 Image registration and noise removed for infrared subpixel-shifted images
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Abstract
For infrared focal plane array sensors, imagery is degraded by a number of phenomena during signal acquisition, particularly including under-sampling and detector non-uniformity. In this paper, we propose an efficient framework which combines neural network non-uniformity correction with image registration for removing structured and non-structured noise and increasing spatial resolution. To achieve this, we sequentially improve the image quality in two steps: primarily, removing the structured and non-structured noise based on neural network theory, and achieving registration using an iterative gradient-based registration technique. Experimental results are presented to demonstrate the effectiveness of the proposed algorithm. By using our method, the shifts between acquired frames are estimated precisely and the quality of reconstructed image is improved.
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Junqi Bai, Junqi Bai, Chunguang Zhao, Chunguang Zhao, Xianya Wang, Xianya Wang, } "Image registration and noise removed for infrared subpixel-shifted images", Proc. SPIE 9142, Selected Papers from Conferences of the Photoelectronic Technology Committee of the Chinese Society of Astronautics: Optical Imaging, Remote Sensing, and Laser-Matter Interaction 2013, 91420N (21 February 2014); doi: 10.1117/12.2054247; https://doi.org/10.1117/12.2054247
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