Signal Activity Estimation with Built-in Noise Management in Raw Digital Images

A. Bosco, Davide Giacalone, A. Bruna, S. Battiato, Rosetta Rizzo
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引用次数: 1

Abstract

Discriminating smooth image regions from areas in which significant signal activity occurs is a widely studied subject and is important in low level image processing as well as computer vision applications. In this paper we present a novel method for estimating signal activity in an image directly in the CFA (Color Filter Array) Bayer raw domain. The solution is robust against noise in that it utilizes low level noise characterization of the image sensor to automatically compensate for high noise levels that contaminate the image signal.
原始数字图像中内置噪声管理的信号活动估计
区分平滑图像区域和显著信号活动区域是一个广泛研究的课题,在低级图像处理和计算机视觉应用中非常重要。在本文中,我们提出了一种新的方法来估计信号活动的图像直接在CFA(彩色滤波阵列)拜耳原始域。该解决方案对噪声具有鲁棒性,因为它利用图像传感器的低水平噪声特性来自动补偿污染图像信号的高噪声水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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