This project explores how unsharp measurements—an advanced quantum technique—can help in detecting image edges using photonic quantum computing. Instead of using traditional digital methods, this approach uses photons (light particles) and quantum beam splitters to process image information in a new way. The system mimics how photons split and interact, and it uses a mathematical model to generate image-like outputs. These outputs are compared with reference images using optimization methods to improve accuracy. To measure how good the results are, we use standard image quality metrics like Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR). The goal is to create a lightweight, accurate, and efficient method for image processing using quantum principles, particularly suited for the next generation of optical computing systems.