基于FPGA的图像自适应AWB系统设计与实现

为了解决常见自动白平衡(Auto White Balance, AWB)方法的场景适应能力不足且实时性较差等问题，提出了一种基于颜色通道直方图重构的自适应AWB方法，并使用现场可编程门阵列(FPGA)对所提出的算法进行硬件电路实现，在校正图像白平衡的同时也确保了系统高速实时处理图像。首先对图像进行限制对比度自适应直方图均衡化(CLAHE)处理来提高图像对比度，然后对图像进行灰度级区间的通道分区统计，对不同场景类别的图像采用颜色直方图匹配或平移的重构方式做自适应处理。实验结果表明，该算法在处理图像白平衡时，相比基于光源估计的AWB算法，色温校正准确率提高了14%,对不同色彩场景有更好的适应性，具有实时处理能力。

Design and Implementation of FPGA-Based Image Adaptive AWB System

In order to solve the problems of insufficient scene adaptability and poor real-time performance of common automatic white balance (AWB) methods, an adaptive AWB method based on color channel histogram reconstruction is proposed, and the hardware circuit of the proposed algorithm is implemented by field programmable gate array (FPGA). It not only corrects the white balance of the image, but also ensures the high-speed real-time image processing of the system. In this method, firstly, the image is processed by restricted limited adaptive histogram equalization (CLAHE) to improve the image contrast, then the channel partition statistics of gray level interval is carried out for the image, and the reconstruction method of color histogram matching or translation is adopted for the images of different scene categories. Experimental results show that compared with AWB algorithm based on light source estimation, the accuracy of color temperature correction of the proposed algorithm is improved by 14%, which has better adaptability to different color scenes and real-time processing ability.