Multiperspective Image Stitching and Regularization via Hybrid Structure Warping

Lu, Yan; Hua, Zizheng; Gao, Kun; Xu, Tingfa

doi:10.1109/mcse.2018.110112927

Cited by 7 publications

(2 citation statements)

References 12 publications

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“…To reduce shape distortion for image stitching, in recent years, similarity transformation has been introduced to reduce the distortions [7][8][9][10][11][12]. Chang et al [7] proposed a shape-preserving half-projective (SPHP) warping for image stitching, which adopted projective transformation to align image, and similarity transformation to achieve gradually change from projective to similarity across the image.…”

Section: Introductionmentioning

confidence: 99%

“…However, some distortions locally still exist when stitching images. Yu et.al [10]proposed a natural image stitching method with the global similarity prior, which constrains the warp of each image so that it resembles a similarity transformation as a whole. They adopt the local warp model and guides the warping of each image with a grid mesh.…”

Section: Introductionmentioning

confidence: 99%

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Feature Points Selection for Rectangle Panorama Stitching

Yan

Wang²,

Yue

et al. 2018

EasyChair Preprints

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Panoramic images can provide users with large view scene, which is widely used in various fields. Image stitching can combine images of adjacent views with small horizon field into a single image with large horizon. Currently stitching method can provide a rectangle panorama by cropped method to view or print. However, this method can occur shape distortion, and information loss. In this paper, we propose a novel shape-optimization method based on feature selection for rectangle panorama. First, to avoid local distortion in overlapping region, the matched feature points is selected by feature cluster analysis. And then, we combine MDLT and derivative warping method to reduce global shape distortion. At last, a quadratic mesh grid optimization model, which is based on boundary constraint and mesh lines constraint, is established to generate rectangle panorama image. Experimental results show that the proposed method can effectively stitch different view image to generate rectangle panorama without ghost, shape distortion and information loss.

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