Robust invariant automatic image mosaicing and super resolution for UAV mapping

A. Nemra, N. Aouf
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引用次数: 9

Abstract

The aim of this paper is to develop efficient, robust and automated image frame fusion algorithms for mosaicing and super-resolution. Image registration is the key step in combining multiple independent low-resolution images to give one large mosaic image with high resolution. Our research is based on Scale Invariant Features Transform (SIFT detector/descriptor) for geometric and photometric images registration for mosaicing. The proposed super-resolution technique is also based on SIFT features and integrated to the image mosaicing in order to construct a full high resolution UAV map that is insensitive to the order, orientation, scale and illumination of the images. Real data validations show the effectiveness of our proposed techniques in comparison with other classical techniques.
基于鲁棒不变自动图像拼接和超分辨率的无人机制图
本文的目的是开发高效、鲁棒和自动化的图像帧融合算法,用于拼接和超分辨率。图像配准是将多幅独立的低分辨率图像组合成一幅高分辨率大拼接图像的关键步骤。我们的研究是基于尺度不变特征变换(SIFT检测器/描述符)的几何和光度图像拼接配准。该超分辨率技术还基于SIFT特征,将其与图像拼接相结合,构建了对图像的顺序、方向、比例和光照不敏感的全高分辨率无人机地图。实际数据验证表明,与其他经典技术相比,我们提出的技术是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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