In the form of images and videos, visual content has always attracted considerable interest and attention to itself since the early days of the computer era. Although, due to the high density of information in such contents, it has always been challenging to generate, process and broadcast videos and images. These challenges grew along with the demand for higher quality content and attained the research community's attention to themselves. Even though many works have been done by researchers and engineers in academic and industrial environments, the demand for high-quality content introduces new constraints on the quality, performance (speed) and energy consumption. This thesis focuses on a couple of image and video processing applications and introduces new approaches and tweaks to improve the performance and save resources while keeping the functionality intact. In the first part, we target Interferometric Synthetic Aperture Radar (InSAR), an imaging technique used by satellites to capture the earth's surface. Many algorithms have been developed to extract useful information, such as height and displacement, from such images. However, the sheer size of these images, along with the complexity of most of these algorithms, lead to very long processing time and resource utilization. In this work, we take one of the dominant algorithms used for almost every In-SAR application, Phase Unwrapping, and introduce an approach to gain up to 6.5 times speedups. We evaluated our method on InSAR images taken by the Radarsat-2 sensor and showed its impact on a real-world application. In the second part of this thesis, we look at a prevalent application, video streaming. These days video streaming dominates the internet traffic, so any slight improvement in terms of energy consumption or resource utilization will make a sizable difference. Although the streamers use various encoding techniques, the quality of experience of the clients prevents them from overplaying these techniques. On the other hand, there has been a growing interest in another venture of research which focuses on developing techniques that aim to restore the quality of the videos that have been subjected to compression. Although these techniques are used by many users on the receiver side, the streamers often ignore their capabilities. In our work, we introduce an approach that makes the streamer aware of the capabilities of the receiver and utilizes that awareness to reduce the cost of transmission without compromising the end user's quality of experience. We demonstrated the technique and proved our concept by applying it to the HEVC encoding standard and JCT-VC dataset. / Graduate