Image Quality Metric

Image quality metrics aim to quantify the perceptual quality of images, often serving as objective measures for comparing different image processing techniques or evaluating the performance of image generation models. Current research focuses on developing robust metrics that accurately reflect human perception, particularly addressing challenges posed by adversarial attacks and the specific needs of diverse applications like medical imaging and video compression. This involves exploring various model architectures, including deep learning-based approaches and adaptations of traditional methods, and benchmarking their performance against subjective evaluations. Improved image quality metrics are crucial for advancing image processing technologies and ensuring reliable evaluation across various domains.