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Super-resolution enhancement of UAV images based on fractional calculus and POCS 被引量:2

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摘要 A super-resolution enhancement algorithm was proposed based on the combination of fractional calculus and Projection onto Convex Sets(POCS)for unmanned aerial vehicles(UAVs)images.The representative problems of UAV images including motion blur,fisheye effect distortion,overexposed,and so on can be improved by the proposed algorithm.The fractional calculus operator is used to enhance the high-resolution and low-resolution reference frames for POCS.The affine transformation parameters between low-resolution images and reference frame are calculated by Scale Invariant Feature Transform(SIFT)for matching.The point spread function of POCS is simulated by a fractional integral filter instead of Gaussian filter for more clarity of texture and detail.The objective indices and subjective effect are compared between the proposed and other methods.The experimental results indicate that the proposed method outperforms other algorithms in most cases,especially in the structure and detail clarity of the reconstructed images.
出处 《Geo-Spatial Information Science》 SCIE CSCD 2018年第1期56-66,共11页 地球空间信息科学学报(英文)
基金 This work is supported by the National Key Research and Development Program of China[grant number 2016YFB0502602] the National Natural Science Foundation of China[grant number 61471272] the Natural Science Foundation of Hubei Province,China[grant number 2016CFB499].
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