A registration algorithm of images with special textures coupling a watershed with mathematical morphology

doi:10.6046/zrzyyg.2021051

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Abstract

Existing registration algorithms suffer low efficiency and accuracy in the registration of synthetic aperture Radar (SAR) and optical images. This study proposed a stepwise refinement-based automatic registration algorithm of images with special textures by coupling marker-controlled watershed segmentation and mathematical morphology. Firstly, the improved marker-controlled watershed algorithm was used to extract the features of water bodies from images, and then binarization and mathematical morphology were applied to accurately extract the water regions. Secondly, the centroids of water bodies were extracted for rough registration between images to improve the search efficiency of the subsequent algorithm. Finally, using the optimization algorithm, the optimal transformation parameters when the similarity measure was maximized were obtained and were used to carry out the spatial transformation of SAR images for image registration. In this manner, the precise registration of SAR and optical images was completed. The experimental results show that the algorithm proposed in this study that couples image segmentation with registration reduced calculation amount while ensuring the registration accuracy. Meanwhile, this algorithm effectively solved the difficulty in the automatic registration of SAR and optical high-resolution images that have large differences in gray levels and spatial resolution.

Keywords SAR image registration mark-controled watershed mathematical morphology special texture

ZTFLH:

TP79

Corresponding Authors: YANG Shuwen E-mail: 1525484225@qq.com;ysw040966@163.com

Issue Date: 14 March 2022

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	Liri ZANG
	Shuwen YANG
	Shunfa SHEN
	Qing XUE
	Xiaowei QIN

Cite this article:

Liri ZANG,Shuwen YANG,Shunfa SHEN, et al. A registration algorithm of images with special textures coupling a watershed with mathematical morphology[J]. Remote Sensing for Natural Resources, 2022, 34(1): 76-84.

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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2021051 OR https://www.gtzyyg.com/EN/Y2022/V34/I1/76

Fig.1 Segmentation results of watershed algorithm

Fig.2 Morphological reconstruction filter

Fig.3 Improved marker-controlled watershed algorithm flow

Fig.4 Morphological processing flow

Fig.5 Overall algorithm flow chart

Fig.6 Image data used in the experiment

Tab.1 Detailed description of experimental data

Tab.3 Precision evaluation of the four segmentation results

Fig.7 SAR-SIFT registration experiment of the first group of images

Fig.8 Heterogeneous image registration experiment of the second group of images

Fig.9 Subjective comparison of experimental results

Tab.4 Quantitative comparison of registration methods

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