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New SAR image segmentation model uses I-divergence-TV approach

Researchers have developed a new variational active contour model for segmenting Synthetic Aperture Radar (SAR) images. This model incorporates an I-divergence-TV approach to handle multiplicative gamma noise, effectively combining edge-based and region-based segmentation techniques. The proposed model is capable of accurately stopping contours at indistinct edges and automatically identifying both external and internal image boundaries. Furthermore, it can be transformed into a generalized ROF model and solved using fast denoising algorithms like BM3D and NLM, offering a unified framework for related subproblems. AI

RANK_REASON The cluster contains a research paper detailing a new algorithm for image segmentation. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.CV →

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New SAR image segmentation model uses I-divergence-TV approach

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The cluster contains a research paper detailing a new algorithm for image segmentation. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Guangming Liu ·

    SAR image segmentation algorithms based on I-divergence-TV model

    arXiv:2312.09365v3 Announce Type: replace Abstract: In this paper, we propose a novel variational active contour model based on I-divergence-TV model to segment Synthetic aperture radar (SAR) images with multiplicative gamma noise, which hybrides edge-based model with region-base…