Seamline optimisation for urban aerial ortho‐image mosaicking using graph cuts

Zhang, Yunsheng; Zhang, Minglei; Du, Shihong; Zou, Zhengrong; Fan, Chong

doi:10.1111/phor.12232

Cited by 9 publications

(10 citation statements)

References 34 publications

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“…Xie and Chen (2019) used a graph‐cut algorithm to search for the initial seam‐line, and then determined whether to update them based on the pixel gradient changes when the moving object passes through the seam‐line. Due to high computational complexity of the graph‐cut algorithm itself (Zhang et al., 2018), it was difficult for the algorithm to regenerate the seam‐line in real time to stitch multiple videos. The same challenge also occurred in using some good image dodging modules (Ding & Ma, 2021; Tian et al., 2016) to eliminate illumination variation between different videos.…”

Section: Related Workmentioning

confidence: 99%

Real‐time generation of spherical panoramic video using an omnidirectional multi‐camera system

Gao,

Wu,

Huang

et al. 2024

The Photogrammetric Record

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This paper presents a novel method for real‐time generation of seamless spherical panoramic videos from an omnidirectional multi‐camera system (OMS). Firstly, a multi‐view video alignment model called spherical projection constrained thin‐plate spline (SP‐TPS) was established and estimated using an approximately symmetrical seam‐line, maintaining the structure inconsistency around the seam‐line. Then, a look‐up table was designed to support real‐time processing of video re‐projection, video dodging and seam‐line updates. In the table, the overlapping areas in OMS multi‐view videos, the seam‐lines between spherical panoramas and OMS multi‐view videos and the pixel coordinate mapping relationship between spherical panoramas and OMS multi‐view videos were pre‐stored as a whole. Finally, a spherical panoramic video was outputted in real‐time through look‐up table computation under an ordinary GPU processor. The experiments were conducted on multi‐view video taken by “1 + 4” and “1 + 7” OMS, respectively. Experimental results demonstrate that compared with four state‐of‐the‐art methods reported in the literature and two bits of commercial software for video stitching, the proposed method excels in eliminating visual artefacts and demonstrates superior adaptability to scenes with varying depths of field. Assuming that OMS is not movable in the scene, this method can generate seamless spherical panoramic videos with a resolution of 8 K in real time, which is of great value to the surveillance field.

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Section: Related Workmentioning

confidence: 99%

Real‐time generation of spherical panoramic video using an omnidirectional multi‐camera system

Gao,

Wu,

Huang

et al. 2024

The Photogrammetric Record

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show abstract

“…Recently, many studies have focused on extracting seamline by analyzing the relationships among image information in overlapping areas and to minimize geometric distortions and mismatches (Li et al, 2018;Zhang et al, 2018;Yuan et al, 2020). Li et al (2018) constructed image energy map using gradient and edge segmentation information and extracted seamline based on graph cut algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Li et al (2018) constructed image energy map using gradient and edge segmentation information and extracted seamline based on graph cut algorithm. Zhang et al (2018) presented a method for optimizing seamline detection in urban aerial image mosaicking using graph cuts. Their technique combined data from Digital Surface Models (DSM) with image color and gradient information to extract seamline, avoiding buildings.…”

Section: Introductionmentioning

confidence: 99%

Development of Multi-Strip Image Mosaicking for KOMPSAT-3A Images

Son,

Park,

Ban

et al. 2024

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. High-resolution satellite imagery has a limitation in terms of coverage area. This limitation presents challenges for extensive-scale analysis at regional or national levels. To maximize the utility of high-resolution satellite imagery, the implementation of image mosaicking techniques is essential. In this paper, we have developed seamline extraction techniques and relative geometric correction optimized for high-resolution satellite imagery. Ultimately, we proposed a multi-strip image mosaicking method for KOMPSAT-3A (Korea Multi-Purpose Satellite-3A) images. We applied the Dijkstra's shortest path algorithm to efficiently extract seamlines. we also performed image registration based on feature matching and homography transformation to correct the relative geometric errors between input images. We conducted experiments with our methods using 29 scenes from KOMPSAT-3A L1G data. The results indicated high relative geometric accuracy, with an average error of 1.63 pixels. Furthermore, we were able to obtain high-quality seamless mosaic images. Our proposed method is expected to enhance the utility of KOMPSAT-3A imagery for large-scale environmental and urban analysis and to provide more accurate and comprehensive data.

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“…However, all related individual orthophotos should be registered with respect to each other, and seamlines in overlapping areas of individual orthophotos should be determined. As a result, the orthophoto mosaic generation can become time-consuming in processing the data, especially when the number of images is large [16]. At the image registration stage, there is a further challenge.…”

Section: Introductionmentioning

confidence: 99%

Automated Two-Step Seamline Detection for Generating Large-Scale Orthophoto Mosaics from Drone Images

Varshosaz,

Sajadian,

Pirasteh

et al. 2024

Remote Sensing

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To generate an orthophoto mosaic from a collection of aerial images, the original images are first orthorectified individually using a Digital Surface Model (DSM). Then, they are stitched together along some determined seamlines to form the orthophoto mosaic. Determining appropriate seamlines is a critical process, as it affects the visual and geometric quality of the results. The stitching process can usually be done in frame-to-frame or multi-frame modes. Although the latter is more efficient, both still involve a lot of pre-processing, such as creating individual orthophotos, image registration, and overlap extraction. This paper presents a novel coarse-to-fine approach that directly determines the seamline network without such pre-processing. Our method has been specifically applied for UAV photogrammetry projects where, due to the large number of images and the corresponding overlaps, the orthophoto mosaic generation can be very challenging and time-consuming. We established the seamlines simultaneously for all the images through a two-step process. First, a DSM was generated, and a low-resolution grid was overlayed. Then, for each grid point, an optimal image was selected. Then, the grid cells are grouped into polygons based on their corresponding optimal image. Boundaries of these polygons established our seamline network. Thereafter, to generate the orthophoto mosaic, we overlayed a higher/full resolution grid on the top of the DSM, the optimal image of each point of which was quickly identified via our low-resolution polygons. In this approach, not only seamlines were automatically generated, but also were the need for the creation, registration, and overlap extraction of individual orthophotos. Our method was systematically compared with a conventional frame-to-frame (CF) technique from different aspects, including the number of double-mapped areas, discontinuities across the seamlines network, and the amount of processing time. The outcomes revealed a 46% decrease in orthophoto generation time and a notable reduction in the number of double-mapped areas, sawtooth effects, and object discontinuities within the constructed orthophoto mosaic.

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Seamline optimisation for urban aerial ortho‐image mosaicking using graph cuts

Cited by 9 publications

References 34 publications

Real‐time generation of spherical panoramic video using an omnidirectional multi‐camera system

Real‐time generation of spherical panoramic video using an omnidirectional multi‐camera system

Development of Multi-Strip Image Mosaicking for KOMPSAT-3A Images

Automated Two-Step Seamline Detection for Generating Large-Scale Orthophoto Mosaics from Drone Images

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