Sequential Far Infrared Image Mosaic Using Coarse-to-Fine Scheme

Tang, Jin; Liang, Yanghui; Guo, Fan; Xiao, Xiaoming

doi:10.1109/access.2019.2918805

Cited by 5 publications

(3 citation statements)

References 25 publications

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“…However, there could be no matches in some subareas due to the sparse or featureless structures. According to Tang's suggestion (Tang et al, 2019), the interior points used to calculate the homography matrix should cover the entire area as much as possible. When the number of sub‐areas with empty blocks (

N

) containing no matched feature points exceeds a threshold

N_{es}

, it indicates that the overlapping areas are homogeneous and rare features are present there.…”

Section: Proposed Sem Image Mosaic Methodsmentioning

confidence: 99%

“…In their study, analyzing the nonlinear deformation of image tiles in overlapping regions allows a more precise alignment to a common geographic coordinate system. Moreover, Tang et al (2019) used a coarse‐to‐fine scheme to optimize the transformation matrix. Sun et al (2006) matched Harris feature points in a constrained search area and automatically estimated optimal geometric and radiometric transformation parameters for microscopy image mosaic.…”

Section: Introductionmentioning

confidence: 99%

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Large‐scale time‐lapse scanning electron microscopy image mosaic using a smooth stitching strategy

Zhao

Zhang

Liu

et al. 2023

Microscopy Res & Technique

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Due to the trade‐off between the field of view and resolution of various microscopes, obtaining a wide‐view panoramic image through high‐resolution image tiles is frequently encountered and demanded in numerous applications. Here, we propose an automatic image mosaic strategy for sequential 2D time‐lapse scanning electron microscopy (SEM) images. This method can accurately compute pairwise translations among serial image tiles with indeterminate overlapping areas. The detection and matching of feature points are limited by geographical coordinates, thus avoiding accidental mismatching. Moreover, the nonlinear deformation of the mosaic part is also taken into account. A smooth stitching field is utilized to gradually transform the perspective transformation in overlapping regions into the linear transformation in non‐overlapping regions. Experimental results demonstrate that better image stitching accuracy can be achieved compared with some other image mosaic algorithms. Such a method has potential applications in high‐resolution large‐area analysis using serial microscopy images. Research Highlights An automatic image mosaic strategy for processing sequential scanning electron microscopy images is proposed. A smooth stitching field is applied in the image mosaic. Improved stitching accuracy is achieved compared with other conventional mosaic methods.

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N

) containing no matched feature points exceeds a threshold

N_{es}

, it indicates that the overlapping areas are homogeneous and rare features are present there.…”

Section: Proposed Sem Image Mosaic Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Large‐scale time‐lapse scanning electron microscopy image mosaic using a smooth stitching strategy

Zhao

Zhang

Liu

et al. 2023

Microscopy Res & Technique

View full text Add to dashboard Cite

show abstract

“…Zhang et al [26] studied the SURF algorithm, which is less complex and more efficient than the SIFT algorithm, and used this algorithm to mosaic panoramic images. Tang et al [27] studied the mosaic algorithm for infrared images. The algorithm combines feature registration and Poisson fusion, has good robustness, is free from noise interference, is simple and effective, and has no splicing gaps.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the Progressive Image Mosaicing Algorithm in Fine Art Image Fusion for Virtual Reality

Song

2021

IEEE Access

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In virtual reality applications, the fade-in and fade-out algorithm based on Bernstein polynomials is a classic method of image fusion. However, this algorithm has certain limitations in image fusion. In this paper, through the analysis and research of the algorithm, the SIFT algorithm is first used to register the image. Secondly, for the disjoint situation of overlapping areas, a progressive image mosaic fusion algorithm in the form of sine function is proposed, which makes it practical and a wider range of applications. It can reflect its characteristics in applications such as virtual reality and art image fusion. Finally, a segmentation technology is added to make the progressive image mosaic fusion algorithm suitable for a variety of overlapping regions, making this algorithm a convenient and flexible image mosaic fusion algorithm. The simulation experiment results show that the progressive mosaic image fusion algorithm proposed in this paper is in good agreement with the spatial details and texture details of highresolution panchromatic images, and the time is shorter, which meets the real-time requirements. INDEX TERMSFine art image fusion; progressive; image mosaic algorithm; virtual reality

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