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Max-RGB Based Colour Constancy Using the Sub-blocks of the Image

机译:使用图像子块的基于最大RGB的颜色恒定性

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Colour constancy refers to the task of revealing the true colour of an object despite ambient presence of intrinsic illuminant. The performance of most of the existing colour constancy algorithms are deteriorated when image contains a big patch of uniform colour. This paper presents a Max-RGB based colour constancy adjustment method using the sub-blocks of the image to significantly reduce the effect of the large uniform colour area of the scene on colour constancy adjustment of the image. The proposed method divides the input image into a number of non-overlapping blocks and computes the Average Absolute Difference (AAD) value of each block's colour component. The blocks with the AADs greater than threshold values are considered having sufficient colour variation to be used for colour constancy adjustment. The Max-RGB algorithm is then applied to the selected blocks' pixels to calculate colour constancy scaling factors for the whole image. Evaluations of the performance of the proposed method on images of three benchmark datasets show that the proposed method outperforms the state of the art techniques in the presence of large uniform colour patches.
机译:颜色恒定性是指尽管周围存在固有发光体,但仍要显示对象的真实颜色的任务。当图像包含大块的均匀颜色时,大多数现有颜色恒定性算法的性能都会下降。本文提出了一种基于Max-RGB的颜色恒定性调整方法,该方法使用图像的子块来显着降低场景的大均匀颜色区域对图像的颜色恒定性调整的影响。所提出的方法将输入图像划分为多个不重叠的块,并计算每个块颜色分量的平均绝对差(AAD)值。 AAD大于阈值的块被认为具有足够的颜色变化,可用于颜色恒定性调整。然后,将Max-RGB算法应用于所选块的像素,以计算整个图像的颜色恒定比例因子。对三个基准数据集的图像上所提出的方法的性能进行的评估表明,在存在较大的均匀色块的情况下,所提出的方法的性能优于现有技术。

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