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Fast shadow removal algorithm for river garbage pollution monitoring system

机译:河流垃圾污染监测系统的快速阴影去除算法

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摘要

In this paper, a fast shadow removal algorithm developed and implemented for river garbage pollution monitoring is reported. The algorithm is a modification of Retinex PDE shadow removal. In usual serial approach way, although giving satisfaction results in removing shadow in river image, Retinex PDE requires much computation tasks. In order to make it run faster, a parallel processing approach was applied. The parallel processing based shadow removal system had been developed using NVIDIA CUDA platform. The shadow removed images will then be processed using image segmentation. The segmentation process will separate between river and non-river (garbage) part in image. To analyze the accuracy of river and garbage separation, the percentages of garbage part in the segmented shadow removed image are compared with the percentage of garbage part obtained from ground truth image. The speed of computation between serial approach and parallel approach of shadow removal are also be compared and analyzed.
机译:本文报道了一种开发并实现的一种用于河流垃圾污染监测的快速阴影去除算法。该算法是Retinex PDE阴影去除的修改。在常规的串行方法中,尽管给出满意的结果会消除河流图像中的阴影,但Retinex PDE仍需要大量计算任务。为了使其运行更快,应用了并行处理方法。基于并行处理的阴影去除系统是使用NVIDIA CUDA平台开发的。然后,将使用图像分割处理去除阴影的图像。分割过程将在图像中河流和非河流(垃圾)部分之间进行分割。为了分析河流和垃圾分离的准确性,将分割的阴影去除图像中垃圾部分的百分比与从地面真实图像获得的垃圾部分的百分比进行比较。比较并分析了串行方法和并行方法去除阴影之间的计算速度。

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