改进型CLAHE图像增强算法及其FPGA实现

Research on the improved CLAHE image enhancement algorithm and its FPGA-based implementation

为解决CLAHE算法硬件资源消耗量大的问题,从硬件实现的角度对算法进行两方面改进。针对裁剪阈值,提出了一种普适性裁剪阈值确定方法,基于信息熵和结构相似性构造了品质因数,以品质因数最佳作为评判标准确定硬件实现中的裁剪阈值,在平衡图像增强对比度和失真度的同时,避免消耗硬件资源对图像数据本身进行大量计算。针对超阈值像素再分配,提出了一种改进型分配方法,将超阈值像素仅均分给未超阈值的灰度级,且若其再次超阈值则停止分配,在降低图像失真度的同时,避免反复像素分配带来的硬件开销。在改进型CLAHE算法的基础上,完成基于FPGA的低照度图像增强系统实现,实验结果表明,在普适性裁剪阈值下,增强后的图像能够普遍获得更高的品质因数,具有更佳的综合效果;改进型像素再分配方法对比常规方法,图像在信息熵平均损失3.28%的代价下结构相似性可平均提升8.88%;低照度图像增强系统可实现640×480@60 fps的图像采集与处理。本设计可为图像增强算法的硬件实现提供一种新的参考。

In order to solve the problem of high hardware resources consumption in the CLAHE algorithm,two improvements are made to the algorithm from the perspective of hardware implementation.For the cropping thresholds,a method for determining the universal clipping threshold is proposed.The Figure Of Merits(FOM)is constructed based on Information Entropy and Structural Similarity,and the clipping threshold in hardware implementation is set using the best FOM as the evaluation criterion to balance the contrast and distortion degree of the image enhancement and avoid consuming hardware resources to perform extensive calculations on the image data itself.For the redistribution of pixels exceeding the threshold,an improved superthreshold pixel redistribution method is proposed,which only distributes pixels to grayscale levels that do not exceed the threshold and stops redistribution if they exceed the threshold again.This method reduce the distortion while avoiding hardware costs caused by repeated pixel distribution.On the basis of the improved CLAHE algorithm,the low illumination image enhancement system based on FPGA is completed.The experimental results show that image enhancement processing based on the universal cropping threshold can generally achieve higher FOM,thus having better overall image enhancement effect.Compared with conventional methods,the improved pixel redistribution method can increase the average SSIM of the image by 8.88%at the cost of an average IE loss of 3.28%.The low light image enhancement system can achieve image acquisition and processing of 640×480@60 fps.This design can provide a new reference for the hardware implementation of image enhancement algorithm.