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Efficient Global Threshold Vector Outlyingness Ratio Filter for the Removal of Random Valued Impulse Noise

机译:高效的全局阈值向量孤立率滤波器,用于去除随机值的脉冲噪声

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摘要

This research paper proposes a filter to remove Random Valued Impulse Noise (RVIN) based on Global Threshold Vector Outlyingness Ratio (GTVOR) that is applicable for real time image processing. This filter works with the algorithm that breaks the images into various decomposition levels using Discrete Wavelet Transform (DWT) and searches for the noisy pixels using the outlyingness of the pixel. This algorithm has the capability of differentiating high frequency pixels and the “noisy pixel” using the threshold as well as window adjustments. The damage and the loss of information are prevented by means of interior mining. This global threshold based algorithm uses different thresholds for different quadrants of DWT and thus helps in recovery of noisy image even if it is 90% affected. Experimental results exhibit that this method outperforms other existing methods for accurate noise detection and removal, at the same time chain of connectivity is not lost.
机译:本文提出了一种基于全局阈值向量孤立率(GTVOR)的随机值脉冲噪声(RVIN)滤波器,该滤波器适用于实时图像处理。该过滤器与算法结合使用,该算法使用离散小波变换(DWT)将图像分解为各种分解级别,并使用像素的孤立性来搜索噪声像素。该算法具有使用阈值以及窗口调整来区分高频像素和“噪点像素”的能力。通过内部采矿可防止损坏和信息丢失。这种基于全局阈值的算法对DWT的不同象限使用不同的阈值,因此即使有90%的噪声图像也可以帮助恢复噪声图像。实验结果表明,该方法优于其他现有方法,可以准确地检测和消除噪声,同时不会丢失连接链。

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