Image and Video Processing

The goal of image and video processing is to enhance the visual quality, extract useful information and improve the quality of the images and videos. This research field includes a wide range of techniques such as image enhancement, object recognition, motion estimation and tracking, image and video coding, quality assessment, and omni-dimensional visual signal processing. Image enhancement techniques are utilized for improving the visual quality of images, for example, by removing noise, improving contrast or restoring images that have been degraded. Object recognition techniques are accustomed to identifying and locating objects within an image or video. Image and video coding seeks to reduce the amount of data required to represent an image or video while preserving its visual quality. This is achieved through various techniques such as spatial and temporal prediction, transform, quantization, and entropy coding. Quality assessment is an important aspect as it involves evaluating the perceived quality of the compressed data in comparison to the original data. Omni-dimensional visual signal processing explores diverse forms of visual data representation that can be processed and analyzed by algorithms, such as light fields for various perspectives and hyperspectral imaging for rich spectrum. Advances in these techniques have led to the wide-ranging applications in various industries such as medical imaging, surveillance and security, autonomous vehicles, entertainment and multimedia, industrial automation and quality control, and communication systems.