Abstract
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.
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