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Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 156-756, Korea





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Abstract In various unmanned aerial vehicle UAV imaging applications, the multisensor super-resolution SR technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution LR images to make a higher resolution HR image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means NLM filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation IHS image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures. View Full-Text

Keywords: multisensor super-resolution SR; UAV image enhancement; regularized image restoration; image fusion multisensor super-resolution SR; UAV image enhancement; regularized image restoration; image fusion





Autor: Wonseok Kang, Soohwan Yu, Seungyong Ko and Joonki Paik *

Fuente: http://mdpi.com/



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