Dynamic Visual Quality Enhancement For Surveillance in Defense Environment

             The Dynamic Visual Quality Enhancement (DVQE) system for surveillance in defense environments effectively addresses the challenges posed by low-light, foggy, or noisy conditions. By integrating deep learning-based image enhancement techniques with real-time video processing, the system significantly improves the clarity, brightness, and contrast of surveillance footage.   Enhanced visual quality allows for more accurate object detection using models such as YOLO, enabling defense personnel to identify vehicles, humans, drones, or suspicious activities with greater reliability. The system also provides quantitative evaluation through metrics like PSNR and SSIM, ensuring that the structural integrity of images is preserved while reducing noise and distortion.   Overall, the DVQE framework offers an intelligent, automated solution for real-time surveillance monitoring, enhancing situational awareness, reducing response times, and supporting more informed decision-making in defense operations. Its modular design, combining acquisition, preprocessing, enhancement, quality assessment, and monitoring, makes it adaptable and scalable for various defense scenarios.

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