BGIR:一个低照明遥感图像恢复算法,基于ZYNQ的实现
Zhihao Guo1,2,3, Liangliang Zheng1,2,3, Wei Xu1,2,3
1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.
Sensors (Basel, Switzerland)
|July 30, 2025
概括
本研究介绍了双边引导图像恢复 (BGIR) 算法,以增强来自互补金属氧化物半导体 (CMOS) 系统的黑暗遥感图像. 在实时应用中,BGIR算法显著提高了图像质量和处理速度.
科学领域:
- 遥感 遥感 遥感 遥感
- 图像处理 图像处理
- 计算机视觉 计算机视觉
背景情况:
- 互补金属氧化物半导体 (CMOS) 成像系统在高率的低光条件下面临限制,导致暗图像,信号噪声比和清晰度差.
- 有效增强遥感图像对于准确的数据解释和分析至关重要.
研究的目的:
- 提出一种新的低光遥感图像增强方法和Zynq (Zynq-7000所有可编程SoC) 硬件设计方案.
- 为了提高在具有挑战性的照明条件下运行的CMOS成像系统所获得的图像的可见性,信号噪声比和清晰度.
主要方法:
- 在色调和值 (HSV) 颜色空间中开发了一种改进的多尺度 Retinex 算法.
- 该方法涉及将RGB分为H,S和V组件,通过双边过处理V组件,应用马校正,并增强S组件.
- 该算法部署在Zynq平台上,使用ARM + FPGA协同作用,结合查找表和加速管道.
主要成果:
- 双边引导图像恢复 (BGIR) 算法显示,与现有方法相比,处理速度提高了近30倍,同时保持了图像质量.
- 端到端部署实现了处理速度为80 fps的640 × 480分辨率和30 fps的1280 × 720分辨率.
- 该解决方案提供了快速处理,小型化,嵌入性和便携性的优势.
结论:
- BGIR算法有效地增强了CMOS系统获得的低光远程传感图像.
- Zynq 硬件实现满足了实时,高速成像应用程序的性能要求.
- 拟议的方法为改善远程传感图像可见性和质量提供了实用和高效的解决方案.
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