An improved adaptive triangular mesh-based image warping method

Tang, Wei; Jia, Fangxiu; Wang, Xiaoming

doi:10.3389/fnbot.2022.1042429

Cited by 5 publications

(5 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the overlapping area 𝛺 𝑜 of 𝐼 1 and 𝐼 2 , the SC method is used to generate a virtual camera, whose viewpoint gradually transitions from the viewpoint of 𝐼 1 to that of 𝐼 2 . 𝑆 4 and 𝑆 5 are the intersection points of the back-projection lines of 𝑢 4 , 𝑢 5 in the visual camera and projection plane $n$, respectively. The virtual camera's image is generated from images 𝐼 1 and 𝐼 2 using perspective transformation.…”

Section: Sc Stitching Processmentioning

confidence: 99%

See 1 more Smart Citation

SC-AOF: A Sliding Camera and Asymmetric Optical Flow-Based Blending Method for Image Stitching

Chang,

Li,

Liang

et al. 2024

Preprint

View full text Add to dashboard Cite

Parallax processing and structure preservation has long been important and challenging tasks in image stitching. In this paper, an image stitching method based on sliding camera to eliminate perspective deformation and asymmetric optical flow to solve parallax is proposed. By maintaining the viewpoint of two input images in the mosaic non-overlapping area and creating a virtual camera by interpolation in the overlapping area, the viewpoint is gradually transformed from one to another image view-point so as to complete the smooth transition of the two image viewpoints and reduce perspective deformation. Two coarsely aligned warped images are generated with the help of a global projection plane. After that, the optical flow propagation and gradient descent method are used to quickly calculate the bidirectional asymmetric optical flow between the two warped images, and the optical flow-based method is used to further align the two warped images to reduce parallax. In the image blending, the softmax function and registration error are used to adjust the width of the blending area, further eliminating ghosting and reduce parallax. Finally, the comparative experiments show that our method can effectively eliminate perspective deformation, reduce misalignment, and save running time.

show abstract

Section: Sc Stitching Processmentioning

confidence: 99%

“…Many solutions have proposed to solve the problems of parallax and perspective deformation in image stitching, so as to improve the quality of stitched images. But most state-of-art mesh-based [3][4][5]and multi-plane [6][7][8] method are time-consuming and vulnerable to false matches.…”

Section: Introductionmentioning

confidence: 99%

SC-AOF: A Sliding Camera and Asymmetric Optical Flow-Based Blending Method for Image Stitching

Chang,

Li,

Liang

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…This is time-consuming and does not allow for emergency response. Strategies based on simultaneous localization and mapping (SLAM) [2][3][4] and inter-frame transformation [5][6][7][8][9][10] offer significant speed advantages but suffer from serious cumulative error problems. Currently, it typically relies on global navigation satellite systems (GNSS) and position orientation system (POS) for rectification and geographic coordinates acquisition [5,6], but this method is less reliable for emergency mapping tasks in extreme environments, such as GNSS denial.…”

Section: Introductionmentioning

confidence: 99%

“…Currently, it typically relies on global navigation satellite systems (GNSS) and position orientation system (POS) for rectification and geographic coordinates acquisition [5,6], but this method is less reliable for emergency mapping tasks in extreme environments, such as GNSS denial. Another approach [7][8][9][10] is to minimize cumulative error through a keyframe selection strategy and multiple optimization strategies to achieve greater robustness. In addition, with the rapid development of deep learning, many researchers have attempted to use end-to-end deep neural networks to learn frame-to-frame transformation relationships to avoid error accumulation [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

SatellStitch: Satellite Imagery-Assisted UAV Image Seamless Stitching for Emergency Response without GCP and GNSS

Wei,

Lan,

et al. 2024

Remote Sensing

View full text Add to dashboard Cite

Rapidly stitching unmanned aerial vehicle (UAV) imagery to produce high-resolution fast-stitch maps is key to UAV emergency mapping. However, common problems such as gaps and ghosting in image stitching remain challenging and directly affect the visual interpretation value of the imagery product. Inspired by the data characteristics of high-precision satellite images with rich access and geographic coordinates, a seamless stitching method is proposed for emergency response without the support of ground control points (CGPs) and global navigation satellite systems (GNSS). This method aims to eliminate stitching traces and solve the problem of stitching error accumulation. Firstly, satellite images are introduced to support image alignment and geographic coordinate acquisition simultaneously using matching relationships. Then a dynamic contour point set is constructed to locate the stitching region and adaptively extract the fused region of interest (FROI). Finally, the gradient weight cost map of the FROI image is computed and the Laplacian pyramid fusion rule is improved to achieve seamless production of the fast-stitch image map with geolocation information. Experimental results indicate that the method is well adapted to two representative sets of UAV images. Compared with the Laplacian pyramid fusion algorithm, the peak signal-to-noise ratio (PSNR) of the image stitching results can be improved by 31.73% on average, and the mutual information (MI) can be improved by 19.98% on average. With no reliance on CGPs or GNSS support, fast-stitch image maps are more robust in harsh environments, making them ideal for emergency mapping and security applications.

show abstract

“…Many solutions have been proposed to solve the problems of parallax and perspective deformation in image stitching, so as to improve the quality of stitched images. But most state-of-the-art mesh-based [3][4][5] and multi-plane [6][7][8] methods are time-consuming and vulnerable to false matches.…”

Section: Introductionmentioning

confidence: 99%

SC-AOF: A Sliding Camera and Asymmetric Optical-Flow-Based Blending Method for Image Stitching

Chang,

Li,

Liang

et al. 2024

Sensors

View full text Add to dashboard Cite

Parallax processing and structure preservation have long been important and challenging tasks in image stitching. In this paper, an image stitching method based on sliding camera to eliminate perspective deformation and asymmetric optical flow to solve parallax is proposed. By maintaining the viewpoint of two input images in the mosaic non-overlapping area and creating a virtual camera by interpolation in the overlapping area, the viewpoint is gradually transformed from one to another so as to complete the smooth transition of the two image viewpoints and reduce perspective deformation. Two coarsely aligned warped images are generated with the help of a global projection plane. After that, the optical flow propagation and gradient descent method are used to quickly calculate the bidirectional asymmetric optical flow between the two warped images, and the optical-flow-based method is used to further align the two warped images to reduce parallax. In the image blending, the softmax function and registration error are used to adjust the width of the blending area, further eliminating ghosting and reducing parallax. Finally, by comparing our method with APAP, AANAP, SPHP, SPW, TFT, and REW, it has been proven that our method can not only effectively solve perspective deformation, but also gives more natural transitions between images. At the same time, our method can robustly reduce local misalignment in various scenarios, with higher structural similarity index. A scoring method combining subjective and objective evaluations of perspective deformation, local alignment and runtime is defined and used to rate all methods, where our method ranks first.

show abstract

An improved adaptive triangular mesh-based image warping method

Cited by 5 publications

References 32 publications

SC-AOF: A Sliding Camera and Asymmetric Optical Flow-Based Blending Method for Image Stitching

SC-AOF: A Sliding Camera and Asymmetric Optical Flow-Based Blending Method for Image Stitching

SatellStitch: Satellite Imagery-Assisted UAV Image Seamless Stitching for Emergency Response without GCP and GNSS

SC-AOF: A Sliding Camera and Asymmetric Optical-Flow-Based Blending Method for Image Stitching

Contact Info

Product

Resources

About