Munaf S, Bharathi A, Jayanthi A N
Department of ECE, Sri Ramakrishna Institute of Technology, Coimbatore, India.
Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam, India.
Sci Rep. 2024 Nov 20;14(1):28770. doi: 10.1038/s41598-024-80339-9.
Advancements in digital imaging and video processing are often challenged by low-light environments, leading to degraded visual quality. This affects critical sectors such as medical imaging, aerospace, and underwater exploration, where uneven lighting can compromise safety and clarity. To enhance image quality in low-light conditions using a computationally efficient system. This paper introduces an FPGA-based system utilizing the Retinex algorithm for low-light image enhancement, implemented on a Coarse-Grained Reconfigurable Architecture (CGRA). The system is designed using Verilog HDL on a Xilinx FPGA, prioritizing hardware optimization to achieve high-quality outputs with minimal latency. The system achieves a processing rate of 60 frames per second (fps) for images with a resolution of 720 × 576. Quantitative evaluations show a Peak Signal-to-Noise Ratio (PSNR) improvement to 43.18 dB, a Structural Similarity Index (SSIM) of 0.92, and a Mean Squared Error (MSE) reduction, demonstrating significant enhancements in image quality. The design also achieves a low power consumption of 0.186 W and efficient resource utilization, with only 2.2% of Slice LUTs and Slice Registers used. The FPGA-based system demonstrates significant improvements in image quality with high computational efficiency, proving beneficial for critical applications in various sectors.
数字成像和视频处理技术的进步常常受到低光照环境的挑战，导致视觉质量下降。这影响到医学成像、航空航天和水下探测等关键领域，在这些领域中，光照不均匀会危及安全和清晰度。为了使用计算效率高的系统在低光照条件下提高图像质量，本文介绍了一种基于现场可编程门阵列（FPGA）的系统，该系统利用视网膜皮层算法进行低光照图像增强，并在粗粒度可重构架构（CGRA）上实现。该系统使用Verilog硬件描述语言在赛灵思FPGA上进行设计，优先考虑硬件优化，以实现具有最小延迟的高质量输出。对于分辨率为720×576的图像，该系统实现了每秒60帧（fps）的处理速率。定量评估显示，峰值信噪比（PSNR）提高到43.18dB，结构相似性指数（SSIM）为0.92，均方误差（MSE）降低，表明图像质量有显著提高。该设计还实现了0.186W的低功耗和高效的资源利用率，仅使用了2.2%的Slice LUT和Slice寄存器。基于FPGA的系统在图像质量上有显著提高，且计算效率高，证明对各个领域的关键应用有益。
