Automatic Matching of Multispectral Images Based on Nonlinear Diffusion of Image Structures

Ruixiang, LI; Zhao, Haitao; Zhang, Xiaoye; Ge, Xiaohua; Yuan, Zhanliang; Zou, Qin

doi:10.1109/jstars.2020.3043379

Cited by 6 publications

(1 citation statement)

References 58 publications

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“…Due to illumination and contrast variation in multispectral image, the performance of descriptor in SIFT alone was not very good. Hence, In remote sensing field, a fusion of SIFT and Gabor feature extractions were proposed [40] [41]. Gabor filter performs well on extracting features in urban and tree areas [42].…”

Section: Multispectral Image Matchingmentioning

confidence: 99%

Multispectral Image Matching Using SIFT and SURF Algorithm: A Review

2023

IJG

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SIFT and SURF image matching were used in many industries such as survey and mapping, geology, medical and automotive. Multispectral sensors offered today become new challenge for researchers to study the performances of SIFT and SURF algorithms on multispectral image. Basically, multispectral image consists of more than three bands. As a result, the differences between those bands leads to nonlinear intensity between images. Both algorithm detectors using ‘blob detector’ that extracting the feature points as a key point for image matching later on. Hence, the less visibility of the feature on the multispectral images was one of the issues need to be solved. Many researchers investigate and propose a new strategy to extract and match the feature point using SIFT and SURF on multispectral image. The image fusions, combinations of different descriptors and revised or alteration of the algorithm themselves were among the approached taken by researchers in order to achieved good results.

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Section: Multispectral Image Matchingmentioning

confidence: 99%

Multispectral Image Matching Using SIFT and SURF Algorithm: A Review

2023

IJG

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Remote Sensing Image Registration Using Fast Visual Saliency and Improved SIFT

Khalili,

Razzazi,

Hosseini

2024

2024 32nd International Conference on Electrical Engineering (ICEE)

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Multimodal Urban Remote Sensing Image Registration Via Roadcross Triangular Feature

Zheng²,

Fang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Automatic image registration of multi-modal urban remote sensing images remains a critical challenging task in remote sensing image analysis due to significant nonlinear radiation distortions between multi-modal image pairs, most of the traditional methods focus on the feature point detection and its local description and ignore the robust road information in multi-modal urban remote sensing images. Motivated by this, we propose a fast and robust registration method for multi-modal urban remote sensing images via road intersection triangular features. The proposed method obtains three main stages: road lines extraction from images, intersection triangular feature construction, and triangular feature matching. The qualitative and quantitative experimental results show that the proposed method significantly outperforms other state-of-the-art methods, even when others completely fail to achieve the registration task of cross-modal images, our method still maintains good robustness and matching efficiency.Index Terms-Multi-modal image registration, road intersection triangular feature, urban remote sensing, image matching.

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Automatic Matching of Multispectral Images Based on Nonlinear Diffusion of Image Structures

Cited by 6 publications

References 58 publications

Multispectral Image Matching Using SIFT and SURF Algorithm: A Review

Multispectral Image Matching Using SIFT and SURF Algorithm: A Review

Remote Sensing Image Registration Using Fast Visual Saliency and Improved SIFT

Multimodal Urban Remote Sensing Image Registration Via Roadcross Triangular Feature

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