蒋菡, 伍俊. 基于二次引导滤波的红外图像增强算法及其FPGA实现[J]. 应用光学, 2023, 44(4): 777-785. DOI: 10.5768/JAO202344.0402002
引用本文: 蒋菡, 伍俊. 基于二次引导滤波的红外图像增强算法及其FPGA实现[J]. 应用光学, 2023, 44(4): 777-785. DOI: 10.5768/JAO202344.0402002
JIANG Han, WU Jun. Infrared image enhancement algorithm based on secondary guided filtering and its implementation on FPGA[J]. Journal of Applied Optics, 2023, 44(4): 777-785. DOI: 10.5768/JAO202344.0402002
Citation: JIANG Han, WU Jun. Infrared image enhancement algorithm based on secondary guided filtering and its implementation on FPGA[J]. Journal of Applied Optics, 2023, 44(4): 777-785. DOI: 10.5768/JAO202344.0402002

基于二次引导滤波的红外图像增强算法及其FPGA实现

Infrared image enhancement algorithm based on secondary guided filtering and its implementation on FPGA

  • 摘要: 针对红外图像细节模糊、对比度低等问题,提出了一种基于二次引导滤波的红外图像增强算法。首先,将原始红外图像作为引导图像,使用引导滤波提取出红外图像的细节信息;其次,将得到的细节信息再进行一次引导滤波处理提取出噪声更低的细节信息;最后,将原始红外图像和两部分的细节信息进行加权求和,实现红外图像增强。该算法能够提高红外图像对比度,增强红外图像细节信息。实验结果表明:相比于其他增强算法,本文算法增强之后的红外图像平均对比度提高了123%~246%,平均梯度提升了56%~101%,视觉效果获得明显改善,更能突显细节特征。基于可编程逻辑门阵列(field programmable gate array, FPGA)实现该算法时,占用资源低,处理640×512像素分辨率的单帧红外图像所需时间可达10.12 ms,能满足红外探测系统的实时性要求,具有一定的实用价值。

     

    Abstract: Aiming at the problems of fuzzy details and low contrast in infrared images, an infrared image enhancement algorithm based on secondary guided filtering was proposed. Firstly, the original infrared image was used as the guided image, and the guided filter was used to extract the detail information of the infrared image. Secondly, the obtained detail information was processed by guided filtering again to extract the detail information with lower noise. Finally, the original infrared image and the details of the two parts were weighted and summed to achieve infrared image enhancement. The proposed algorithm can improve the contrast and the details of the infrared images. Experimental results show that, compared with other enhancement algorithms, the average contrast and the average gradient of infrared images enhanced by the proposed algorithm is increased by 123% to 246% and 56% to 101%, respectively. The visual effect is significantly improved, and the details can be highlighted more clearly. Implementing the proposed algorithm based on field programmable gate array (FPGA) has low resource consumption. It takes up to 10.12 ms to process the single-frame infrared image with 640×512 resolution, which can meet the real-time requirements of the infrared detection system and has certain practical values.

     

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