A New Search Algorithm Based on Muti-Octagon-Grid

To cope with the defects of the fast search algorithms based on the UESA (unimodal error surface assumption) that can easily lead to a local minimum or wrong search direction and on the analysis of the characteristics of many kinds of motion sequences, a new search algorithm based on the Muti-Octogon-Grid (MOGS) is proposed. The algorithm takes adaptive search strategies by using the distribution characteristics of motion vector and some other technologies, such as the adaptive threshold of macro-block and dynamic search range. Experimental results show that, compared with the UMHexagonS and Full Search, the algorithm maintains the same image quality and bit-rate, but it makes great improvement on the search speed and encoding time. The PSNR (Peak Signal-toNoise Ratio) increases about 0.004dB, the SIR (the Speed Improvement Rate) is 42% and 91%, the encoding time can be reduced by 21% and 78%, only with the bit-rate increased by 2.1% and 3.0% respectively on average.