基于暗通道先验的红外图像清晰化及FPGA实现

Infrared image clarifying and FPGA implementation based on dark channel prior

针对红外图像普遍存在目标与背景对比度低、细节模糊等问题,提出一种改进的基于暗通道先验理论的红外图像清晰化算法,并在FPGA平台加以设计实现。该算法通过对输入图像当前像素和邻域的数据进行非线性滤波得到暗通道图像数据,并利用修正函数对透射率进行优化生成透射率查找表。在此基础上,根据暗通道像素值在查找表中查找透射率,并结合大气光散射模型进行图像清晰化处理,从而减少或消除传统暗通道算法产生的块效应及天空等高亮区域的颜色失真。结果表明,处理后的红外图像细节特征丰富、明亮度适宜。所提算法基于FPGA硬件实现仅占用4%的LUT和8%的I/O资源,工作频率最高达188 MHz,远远高于所使用的红外相机工作频率27 MHz,能够满足实时处理视频图像的需求。

In order to solve the problem of low contrast between the target and the background and blurred details in infrared images,an improved infrared image clearing algorithm based on dark channel prior theory was proposed and FPGA was used to design the hardware system of the proposed algorithm.The dark channel image was obtained based on nonlinear filtering of the current pixel and the neighborhood data of the input image.Moreover,the correction function was used to optimize the transmission to generate a lookup table.Then the transmission was looked up in the lookup table and the proposed algorithm enhanced the image with the atmospheric scattering model,thereby reducing or eliminating the block effects and the color distortion of the sky or other bright areas generated by the traditional dark channel algorithm.The design of FPGA hardware could work with an estimated frequency of 188 MHz by occupying only 4%of LUT and 8%of I/O resources,which was much higher than the operating frequency of 27 MHz of the camera used.Therefore,the design was realized to meet the requirements of real-time application of video images.