Color adaptation of videos for mobile devices

• Main Author: Ang, Fu Li
• Other Authors: Deepu Rajan
• Format: Final Year Project
• Language: English
• Published: 2009
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
• Online Access: http://hdl.handle.net/10356/16880
• Institution: Nanyang Technological University

As technology improves rapidly over the recent years, watching videos on mobile devices is no longer a dream. In the past, videos are, more often than not, only played on television or personal computers. Nowadays, the improvements in technology have made the playback of videos on mobile devices possible. However, this is not without any problems. In terms of video quality, videos that are played on mobile devices still pales in comparison with videos played on television or personal computers. This Final Year Project (FYP) aims to investigate and analyze the different algorithms that can be used to improve the color adaptation of video process on mobile devices. This is done by conducting experiments on images using the different algorithms and then analyzing which algorithm is suitable to carry out the video adaptation process. The project implementation consists of three main parts: adaptation for grayscale displays, adaptation for binary displays and video adaptation. The different algorithms have been implemented on images and the advantages and disadvantages of the different algorithms have been highlighted. The algorithms were then extended to videos. It was found that although some of the methods work well for images, they do not work very well for video. An example would be the Floyd-Steinberg algorithm. The results obtained from this project highlighted the suitability of the different algorithms for image and video adaptation. Currently, the focus is on grayscale and binary images and videos. Future research can be conducted on color images and videos. In addition, real-time transferring of videos to mobile devices can also be done to examine the other factors that might affect the quality of videos in mobile devices.