Screen content has become one of the prominent mediums in increasingly connected world. With prevalence remote collaboration and communication such as virtual conferences online education, recent years have witnessed a dramatic increase data volume screen content. compression serves fundamental technology fostering storage, transmission, exhibition In this article, we target super-resolution co...

Since the first success of Dong et al., deep-learning-based approach has become dominant in field single-image super-resolution. This replaces all handcrafted image processing steps traditional sparse-coding-based methods with a deep neural network. In contrast to methods, which explicitly create high/low-resolution dictionaries, dictionaries are implicitly acquired as nonlinear combination mul...

Super-resolution is the task of obtaining a high-resolution image of a scene given low resolution image(s) of the scene. Applications of super-resolution include forensic, satellite, medical imaging, surveillance, displaying video on large screens, etc [1]. Obtaining high-resolution images directly via better hardware (better image sensors, larger chip size) is quite costly. Furthermore, most o...

Binary image classification is a problem that has received much attention in recent years. In this paper we evaluate a selection of popular techniques in an effort to find a feature set/classifier combination which generalizes well to full resolution image data. We then apply that system to images at one-half through onesixteenth resolution, and consider the corresponding error rates. In additi...

Image super-resolution is the task of obtaining a high-resolution (HR) image of a scene given low-resolution (LR) image(s) of the scene. In this project, we have focused on the task of super-resolution given a single LR image, which is usually the case. There exist many techniques in literature addressing this task, and we have considered two techniques having the essence of [1] and [2]. In fir...

The extraction of a single high-quality image from a set of low-resolution images is an important problem which arises in fields such as remote sensing, surveillance, medical imaging and the extraction of still images from video. Typical approaches are based on the use of cross-correlation to register the images followed by the inversion of the transformation from the unknown high resolution im...