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Real-time auto white balancing using DWT-based multi-scale clustering

机译:使用基于DWT的多尺度群集进行实时自动白平衡

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Auto white balancing (AWB) involves the process of making white colors to appear as white under different illuminants in digital imaging products such as digital still cameras. This paper presents a computationally efficient auto white balancing algorithm for real-time deployment in imaging products. The algorithm utilizes DWT (discrete wavelet transform) to perform multi-scale clustering (MSC), thus generating a computationally efficient implementation of the original MSC algorithm. The paper also discusses the steps taken to allow running this algorithm in real-time on a digital camera processor. The results of an actual implementation on the Texas Instruments TMS320DM320 processor are provided to illustrate the effectiveness of this algorithm in identifying an illuminant as compared to the widely used gray-world auto white balancing algorithm.
机译:自动白平衡(AWB)涉及在白色数码相机等数字成像产品中,使白色在不同光源下显示为白色的过程。本文提出了一种在成像产品中实时部署的计算有效的自动白平衡算法。该算法利用DWT(离散小波变换)执行多尺度聚类(MSC),从而生成了原始MSC算法的高效计算实现。本文还讨论了允许在数字相机处理器上实时运行此算法的步骤。提供了德州仪器(TI)TMS320DM320处理器上的实际实现结果,以说明与广泛使用的灰度世界自动白平衡算法相比,该算法在识别光源方面的有效性。

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