Underwater Image Enhancement Using Pre-trained Transformer

The goal of this work is to apply a denoising image transformer remove the distortion from underwater images and compare it with other similar approaches. Automatic restoration plays an important role since allows increase quality images, without need for more expensive equipment. This critical example machine learning algorithms support marine exploration monitoring, reducing human intervention like manual processing thus saving time, effort, cost. paper first application transformer-based approach called “Pre-Trained Image Processing Transformer” images. tested on UFO-120 dataset, containing 1500 corresponding clean