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Multidomain Pixel Analysis for Illuminant Estimation and Compensation

机译:发光体估计和补偿的多域像素分析

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The illuminant estimation has an important role in many domain applications such as digital still cameras and mobile phones, where the final image quality could be heavily affected by a poor compensation of the ambient illumination effects. In this paper we present an algorithm, not dependent on the acquiring device, for illuminant estimation and compensation directly in the color filter array (CFA) domain of digital still cameras. The proposed algorithm takes into account both chromaticity and intensity information of the image data, and performs the illuminant compensation by a diagonal transform. It works by combining a spatial segmentation process with empirical designed weighting functions aimed to select the scene objects containing more information for the light chromaticity estimation. This algorithm has been designed exploiting an experimental framework developed by the authors and it has been evaluated on a database of real scene images acquired in different, carefully controlled, illuminant conditions. The results show that a combined multi domain pixel analysis leads to an improvement of the performance when compared to single domain pixel analysis.
机译:发光体估计在许多域应用中具有重要作用,例如数字静态摄像机和移动电话,其中最终的图像质量可能受到环境照明效果的差的差的差的影响。在本文中,我们介绍了一种算法,不依赖于获取设备,用于直接在数字静止摄像机的滤色器阵列(CFA)域中的发光体估计和补偿。所提出的算法考虑了图像数据的色度和强度信息,并通过对角线变换执行发光剂补偿。它通过将空间分割过程与经验设计的重量函数组合,旨在选择包含灯光色度估计更多信息的场景对象。该算法已经设计利用作者开发的实验框架,并且已经在不同,仔细控制,发光条件下获取的真实场景图像的数据库中进行了评估。结果表明,与单域像素分析相比,组合的多域像素分析导致改善性能。

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