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

机译:DEWAFF:一种提高单元跟踪系统性能的新型图像抽象方法

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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,旨在改善典型的图像相关模式识别任务,例如分段,跟踪和分类。所提出的图像抽象框架执行图像去噪和均匀区域简化,以及边界和区域增强。所提出的框架包括一种新的常见加权平均去噪算法的新的通用方法,与Unsharp掩蔽(USM)边界增强技术混合,以避免典型的USM伪像作为振铃。提出了用于小区跟踪应用程序的图像抽象框架内的不同配置的结果。

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