Multiscale watershed segmentation of multivalued images

2003 ◽  
Author(s):  
P. Scheunders ◽  
J. Sijbers
Keyword(s):  
Watershed Segmentation ◽  
Multivalued Images

Laplace watershed segmentation based on minimum energy

2009 ◽  
Vol 29 (2) ◽  
pp. 462-464 ◽  
Author(s):  
Hui-jun FENG ◽  
Bin CHEN ◽  
Xiang-hui ZHAO ◽  
Fan XIA
Keyword(s):  
Minimum Energy ◽  
Watershed Segmentation

scholarly journals A Watershed-Segmentation-Based Improved Algorithm for Extracting Cultivated Land Boundaries

2021 ◽  
Vol 13 (5) ◽  
pp. 939
Author(s):  
Yongan Xue ◽  
Jinling Zhao ◽  
Mingmei Zhang
Keyword(s):  
Color Space ◽  
Cultivated Land ◽  
Color Spaces ◽  
Region Merging ◽  
Watershed Segmentation ◽  
Coverage Area ◽  
Time Efficiency ◽  
Image Contrast Enhancement ◽  
Segmentation Accuracy ◽  
Rgb Color Space

To accurately extract cultivated land boundaries based on high-resolution remote sensing imagery, an improved watershed segmentation algorithm was proposed herein based on a combination of pre- and post-improvement procedures. Image contrast enhancement was used as the pre-improvement, while the color distance of the Commission Internationale de l´Eclairage (CIE) color space, including the Lab and Luv, was used as the regional similarity measure for region merging as the post-improvement. Furthermore, the area relative error criterion (δA), the pixel quantity error criterion (δP), and the consistency criterion (Khat) were used for evaluating the image segmentation accuracy. The region merging in Red–Green–Blue (RGB) color space was selected to compare the proposed algorithm by extracting cultivated land boundaries. The validation experiments were performed using a subset of Chinese Gaofen-2 (GF-2) remote sensing image with a coverage area of 0.12 km2. The results showed the following: (1) The contrast-enhanced image exhibited an obvious gain in terms of improving the image segmentation effect and time efficiency using the improved algorithm. The time efficiency increased by 10.31%, 60.00%, and 40.28%, respectively, in the RGB, Lab, and Luv color spaces. (2) The optimal segmentation and merging scale parameters in the RGB, Lab, and Luv color spaces were C for minimum areas of 2000, 1900, and 2000, and D for a color difference of 1000, 40, and 40. (3) The algorithm improved the time efficiency of cultivated land boundary extraction in the Lab and Luv color spaces by 35.16% and 29.58%, respectively, compared to the RGB color space. The extraction accuracy was compared to the RGB color space using the δA, δP, and Khat, that were improved by 76.92%, 62.01%, and 16.83%, respectively, in the Lab color space, while they were 55.79%, 49.67%, and 13.42% in the Luv color space. (4) Through the visual comparison, time efficiency, and segmentation accuracy, the comprehensive extraction effect using the proposed algorithm was obviously better than that of RGB color-based space algorithm. The established accuracy evaluation indicators were also proven to be consistent with the visual evaluation. (5) The proposed method has a satisfying transferability by a wider test area with a coverage area of 1 km2. In addition, the proposed method, based on the image contrast enhancement, was to perform the region merging in the CIE color space according to the simulated immersion watershed segmentation results. It is a useful attempt for the watershed segmentation algorithm to extract cultivated land boundaries, which provides a reference for enhancing the watershed algorithm.

scholarly journals TPVTrack v1.0: a watershed segmentation and overlap correspondence method for tracking tropopause polar vortices

2018 ◽  
Vol 11 (12) ◽  
pp. 5173-5187 ◽  
Author(s):  
Nicholas Szapiro ◽  
Steven Cavallo
Keyword(s):  
Software Package ◽  
Unstructured Grids ◽  
Test Cases ◽  
Watershed Segmentation ◽  
Spatial Characterization ◽  
Modular Software ◽  
Mean Structure ◽  
Spatial Shape ◽  
Physical Features ◽  
Effective Representation

Abstract. A new free modular software package is described for tracking tropopause polar vortices (TPVs) natively on structured or unstructured grids. Motivated by limitations in spatial characterization and time tracking within existing approaches, TPVTrack mimics the expected dynamics of TPVs to represent their (1) spatial structure, with variable shapes and intensities, and (2) time evolution, with mergers and splits. TPVs are segmented from the gridded flow field into spatial objects as restricted regional watershed basins on the tropopause, described by geometric metrics, associated over time by overlap similarity into major and minor correspondences, and tracked along major correspondences. Simplified segmentation and correspondence test cases illustrate some of the appeal, sensitivities, and limitations of TPVTrack, including effective representation of spatial shape and reduced false positive associations in time. Tracked TPVs in more realistic historical conditions are consistent in bulk with expectations of life cycle and mean structure. Individual tracks are less reliable when discriminating among multiple overlaps. Modifications to track other physical features are possible, with each application requiring evaluation.

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