Aerial Image Stitching Based on Fusion of Geographic Coordinates and Image Features

Guo, Liangchao; Zhu, Huyang; Liu, Yuwei; Sun, Xiaoliang; Teng, Xichao

doi:10.1109/icus55513.2022.9986913

Cited by 1 publication

(1 citation statement)

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“…Image stitching is the process of fusing several original images with fields of overlap into a single high-definition image with a broad view through a stitching algorithm, which mainly includes the processes such as feature matching, image warping, and image fusion. It has exerted a significant influence on the field of computer vision and has an extensive range of applications in virtual reality, aerial image processing, and geological drilling [1][2]. Zaragoza et al proposed an As-Projective-As-Possible (APAP) [3] warping, which divides the image into several grids for alignment and opens a new horizon for the development of image alignment algorithms.…”

Section: Introductionmentioning

confidence: 99%

Image stitching method based on feature optimization and circular function weighted fusion

Hou

Jiang

Xia

et al. 2023

J. Phys.: Conf. Ser.

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To address the issues of ghosting and chromatic gaps in parallax image stitching, this paper proposes a novel method based on feature optimization and circular function weighted fusion. The method employs the Scale-Invariant Feature Transform (SIFT) algorithm with dimensionality reduction optimization to extract point features, while the Grid-based Motion Statistics (GMS) algorithm is utilized to eliminate mismatched points. To further enhance the number of features, line features are also introduced. A local warping model is employed to guide the deformation of the grid image. Finally, a nonlinear fading-in and fading-out fusion model with circular function weighting is proposed for better image transition. Experimental results demonstrate that the proposed method is effective in dealing with ghosting and chromatic gaps compared to several existing methods.

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Section: Introductionmentioning

confidence: 99%