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用于检测图像序列中无阴影场景变化的噪声边界方法。

Noise-bound method for detecting shadow-free scene changes in image sequences.

作者信息

Irie Kenji, McKinnon Alan, Unsworth Keith, Woodhead Ian

机构信息

Lincoln Ventures Ltd, P.O. Box 133, Lincoln, Christchurch 7640, New Zealand.

出版信息

J Opt Soc Am A Opt Image Sci Vis. 2010 Feb 1;27(2):167-73. doi: 10.1364/JOSAA.27.000167.

Abstract

Many image processing applications are confounded by both sensor noise and cast shadows. All image sensors add noise to a captured image that can reduce algorithm sensitivity and performance, and global filters or fixed thresholds are often applied to limit their effects. Cast shadows can appear as scene changes and are difficult to adequately detect and remove from images and image sequences. We couple image-noise statistics with a dual-illumination shadow-detection algorithm to provide a novel color-based method for shadow-free scene-change detection whose performance is bound by metamerism and image noise, and has only one variable--the desired confidence interval for noise separation.

摘要

许多图像处理应用程序都会受到传感器噪声和投射阴影的困扰。所有图像传感器都会给捕获的图像添加噪声,这可能会降低算法的灵敏度和性能,因此通常会应用全局滤波器或固定阈值来限制其影响。投射阴影可能会表现为场景变化,并且很难从图像和图像序列中充分检测和去除。我们将图像噪声统计与双光照阴影检测算法相结合,以提供一种新颖的基于颜色的无阴影场景变化检测方法,其性能受同色异谱和图像噪声的限制,并且只有一个变量——噪声分离所需的置信区间。

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