Nr Iqa

No-Reference Image Quality Assessment (NR-IQA) aims to automatically evaluate the perceived quality of an image without needing a pristine reference image, a crucial task for various applications like photo curation and mobile image processing. Current research focuses on developing lightweight, efficient deep learning models—often employing transformer, convolutional neural network, or state-space model architectures—that accurately predict human judgments of image quality, even on high-resolution images and mobile devices. This field is vital for improving image processing algorithms, optimizing image compression techniques, and enhancing user experience in applications dealing with large numbers of images.