Acceleration method of infrared image detail enhancement on FPGA

一种基于FPGA的红外图像细节增强加速方法

School of Computer Science, Northwestern Polytechnical University, Xi’an 710072, China

Received: 24 September 2021

Abstract

Among the many cockpit human-computer interaction systems of airborne, vehicle-mounted, and ship-borne platforms, the image detail enhancement technology can improve the ability of personnel to interpret infrared images, which has very important application requirements. The enhanced algorithm running on the embedded computing platform needs to have a higher processing speed and smaller time delay in meeting the needs of real-time interaction. The current infrared video sensor usually has a lower resolution, and the image detail enhancement algorithm still can achieve real-time processing performance on a homogeneous multi-core CPU processing platform. However, as the resolution of platform sensors continues to increase, image processing speed and time delay are difficult to meet application requirements. We propose a method for enhancing and accelerating infrared image details for FPGA platforms. By considering the FPGA's specific domain software and hardware computing architecture, the traditional bilateral filtering image details algorithm is accelerated using local cache and search table, so that real-time processing performance can still be achieved under the input image of the 4k resolution, while almost no additional memory access delay is added. While ensuring the processing effect, the algorithm greatly improves the processing and delay indicators to meet the application requirements of embedded equipment in specific fields such as the cockpit human-computer interaction system.

摘要

在机载、车载、舰载平台的众多座舱人机交互系统中, 图像细节增强能够提升人员对红外图像的判读能力, 具有非常重要的应用需求。运行在嵌入式计算平台上的增强算法需要具有较高的处理速度和较低的算法延迟才能满足实时交互的需求。当前红外视频传感器分辨率较低, 图像细节增强算法在同构多核CPU处理平台上即可达到实时处理性能。然而, 随着平台传感器分辨率的持续增加, 图像处理速度和延迟难以满足。提出一种针对FPGA平台的红外图像细节增强加速方法, 考虑FPGA的特定领域软硬件计算架构, 采用基于局部缓存和查表等方式对传统的双边滤波图像细节算法进行加速, 使得在4k分辨率输入图像下, 依然能够达到实时处理性能, 同时几乎不增加额外的访存延迟。算法在保证处理效果的同时, 极大地提升了处理和延迟指标, 满足座舱人机交互系统等嵌入式装备特定领域应用需求。