多尺度Retinex低照度图像增强的ZYNQ实现

Implementation of Low-illumination Image Enhancement Based on Multi-scale Retinex on ZYNQ

针对头戴夜视系统低照度图像增强的实时处理需求,给出了一种基于改进的多尺度Retinex图像增强算法的硬件化方法。将输入的低照度灰度图像分解为照度分量和反射分量;以具有保边特性的双边滤波函数作为多尺度Retinex模型的中心环绕函数,完成照度分量的估计,进而得到输出反射图;采用限制对比度自适应直方图均衡化方法拉伸图像灰度级,限制对比度过度增加并抑制噪声;选用Xilinx公司的ZYNQ开发套件,实现了基于流水线和并行处理技术的算法硬件移植。仿真分析和测试实验表明,硬件平台能够有效提升低照度图像的亮度和对比度,恢复更多图像细节信息,图像增强客观评价指标与仿真结果接近,可满足头戴夜视系统的使用要求。

Aiming at the real-time processing requirement of low-illumination image enhancement in head-mounted night vision system,a hardware method based on improved multi-scale Retinex algorthm for image enhancement is presented.Firstly,the input low-illumination gray image is decomposed into illumination component and reflection component.Secondly,the edge-preserving bilateral filter function is used as the central circumferential function of the multi-scale Retinex model,and then the illumination component is estimated,and the output reflection image is finally obtained.Then the image gray level is stretched by the equalization method of contrast limited adaptive histogram to limit the excessive increase of contrast and suppress the noise.Finally,the algorithm hardware transplantation based on pipeline and parallel processing technology is implemented on the ZYNQ development kit of Xilinx company.The simulation analysis and test experiments show that the hardware platform can effectively enhance the brightness and contrast of low-illumination images,and can recover more image details.The objective evalution index of image enhancement is close to the simulation results,which can meet the real-time processing requirements of head-mounted night vision system.