Automatic Satellite Image Stitching Based on Speeded Up Robust Feature

V. Megha, K. Rajkumar
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引用次数: 5

Abstract

The process of merging multiple images those having overlapping areas and covering different views of the same scene into a composite image is called image stitching. Image stitching can be used in variety of applications such as computer vision, medical image analysis, satellite imaging, photogrammetry etc. Image stitching also used for creating mosaic images which is useful for extending the field of view of the image. Image stitch are generally classified into direct image stitching and feature based image stitching. In this paper we proposed a feature-based satellite image stitching using Speeded Up Robust Features (SURF) algorithm. SURF mainly involves two steps, feature point detection and feature description. Detected feature points of input images are compared using nearest neighbourhood matching for identifying the overlapping points. Affine transformation-based image warping is used for aligning the input images to the mosaic frame. Finally, alpha blending is used for making the final mosaic as perfect smooth image.
基于加速鲁棒特征的卫星图像自动拼接
将具有重叠区域和覆盖同一场景不同视图的多幅图像合并成合成图像的过程称为图像拼接。图像拼接可用于计算机视觉、医学图像分析、卫星成像、摄影测量等多种应用。图像拼接也用于创建马赛克图像,这对于扩展图像的视场是有用的。图像拼接一般分为直接图像拼接和基于特征的图像拼接。本文提出了一种基于加速鲁棒特征(SURF)算法的卫星图像拼接方法。SURF主要包括特征点检测和特征描述两个步骤。利用最近邻匹配对输入图像检测到的特征点进行比较,识别重叠点。基于仿射变换的图像翘曲用于将输入图像对准拼接帧。最后,alpha混合用于使最终的马赛克成为完美的平滑图像。
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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