Title: Motion Compensation Methods in Wavelet Based Video Coding
Ayesha Farrukh

Abstract: It is widely recognised that compression is essential for virtually all applications involving the transmission or storage of digital video media. Motion compensation provides a considerable amount of compression during video coding, without it, the sheer volume of video data would be impractical to store, transmit or handle. Having a powerful compression scheme alone, however, may not be the complete solution to some applications such as image/video database browsing and multipoint video distribution over heterogeneous networks. There is also a growing need for other useful features such as video scalability. The development of efficient scalable video compression requires a major shift in the video coding paradigm. The next generation of video coders will offer both compression and scalability - wavelet based video coding promises exactly this. This thesis will investigate recent trends in motion compensation in wavelet based video coding. Currently these techniques give equal or better performance as standardized coders but are inefficient in terms of memory usage and coding speed. These issues will be examined in this work. The topics covered will be scalable video coding, the 3D discrete wavelet transform, lifting, motion compensated wavelet coding, motion compensated temporal filtering (MCTF), and scalable coding of motion information.