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DeWAFF: A novel image abstraction approach to improve the performance of a cell tracking system

机译:DeWAFF:一种新颖的图像抽象方法,可提高细胞跟踪系统的性能

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摘要

This paper presents a new image abstraction approach, aiming to improve typical image related pattern recognition tasks such as segmentation, tracking, and classification. The proposed image abstraction framework performs image denoising and homogeneous region simplification, along with border and region enhancement. The proposed framework consists in a novel generalized approach of common weighted averaging denoising algorithms mixed with Unsharp Masking (USM) border enhancement techniques, to avoid typical USM artifacts as ringing. Results of the different configurations within the image abstraction framework for a cell tracking application are presented.
机译:本文提出了一种新的图像抽象方法,旨在改善与图像相关的典型模式识别任务,例如分割,跟踪和分类。所提出的图像抽象框架执行图像去噪和均质区域简化,以及边界和区域增强。所提出的框架包括一种新颖的通用加权平均降噪算法的通用方法,该算法结合了非锐化屏蔽(USM)边界增强技术,以避免出现典型的USM伪像。提出了用于细胞跟踪应用的图像抽象框架内不同配置的结果。

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