This thesis presents the rate distortion analysis of conditional motion estimation, a process in which motion computation is restricted to only active pixels in the video. We model active pixels as independent and identically distributed Gaussian process and inactive pixels as Gaussian-Markov process and derive the rate distortion function based on conditional motion estimation. Rate-Distortion curves for the conditional motion estimation scheme are also presented. In addition this thesis also presents the hardware implementation of a block based motion estimation algorithm. Block matching algorithms are difficult to implement on FPGA chip due to its complexity. We implement 2D-Logarithmic search algorithm …
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This thesis presents the rate distortion analysis of conditional motion estimation, a process in which motion computation is restricted to only active pixels in the video. We model active pixels as independent and identically distributed Gaussian process and inactive pixels as Gaussian-Markov process and derive the rate distortion function based on conditional motion estimation. Rate-Distortion curves for the conditional motion estimation scheme are also presented. In addition this thesis also presents the hardware implementation of a block based motion estimation algorithm. Block matching algorithms are difficult to implement on FPGA chip due to its complexity. We implement 2D-Logarithmic search algorithm to estimate the motion vectors for the image. The matching criterion used in the algorithm is Sum of Absolute Differences (SAD). VHDL code for the motion estimation algorithm is verified using ISim and is implemented using Xilinx ISE Design tool. Synthesis results for the algorithm are also presented.
This thesis is part of the following collection of related materials.
UNT Theses and Dissertations
Theses and dissertations represent a wealth of scholarly and artistic content created by masters and doctoral students in the degree-seeking process. Some ETDs in this collection are restricted to use by the UNT community.