Super-resolution (SR) refers to the process of taking one or more low-resolution (LR) images and generating a high-resolution (HR) output. When "Optimization" is added, it emphasizes making these models efficient for real-world deployment, balancing trade-offs between accuracy, inference time, and computational cost.
True IMGSRRO is not about maximizing one metric in a vacuum. It is about the entire pipeline for the real world: training efficiency, inference latency, memory footprint, and visual quality as perceived by humans or downstream tasks. imgsrro
Modern IMGSRRO uses , e.g.:
[ I_LR = D(I_HR; \theta) + n ]
[ L_total = L_pixel + \lambda_1 L_perceptual + \lambda_2 L_adversarial + \lambda_3 L_edge ] Super-resolution (SR) refers to the process of taking