An adaptive true motion estimation algorithm for frame rate up-conversion and its hardware design

Official URL: http://192.168.1.20/record=b1301497 (Table of Contents)

With the advancement in video and display technologies, recently flat panel High Definition Television (HDTV) displays with 100 Hz, 120 Hz and most recently 240 Hz picture rates are introduced. However, video materials are captured and broadcast in different temporal resolutions ranging from 24 Hz to 60 Hz. In order to display these video formats correctly on high picture rate displays, new frames should be generated and inserted into the original video sequence to increase its frame rate. Therefore, Frame Rate Up-Conversion (FRUC) has become a necessity. Motion Compensated FRUC algorithms provide better quality results than non-motion compensated FRUC algorithms. Motion Estimation (ME) is the process of finding motion vectors which describe the motion of the objects between adjacent frames and is the most computationally intensive part of motion compensated FRUC algorithms. For FRUC applications, it is important to find the motion vectors that represent real motions of the objects which is called true ME. In this thesis, an Adaptive True Motion Estimation (ATME) algorithm is proposed. ATME algorithm produces similar quality results with less number of calculations or better quality results with similar number of calculations compared to 3-D Recursive Search true ME algorithm by adaptively using optimized sets of candidate search locations and several redundancy removal techniques. In addition, 3 different complexity hardware architectures for ATME are proposed. The proposed hardware use efficient data re-use schemes for the non-regular data flow of ATME algorithm. 2 of these hardware architectures are implemented on Xilinx Virtex-4 FPGA and are capable of processing ~158 and ~168 720p HD frames per second respectively.