Motion Estimation (ME) is an integral part of any video encoder and a large number of Block Matching Motion Estimation (BMME) Algorithms are proposed to cope the computational complexity and increase quality of ME process requirement. Therefore, it is necessary to evaluate the performance of these ME algorithms for different motion activities. In this paper five fast famous BMME algorithms are considered to evaluate their performance on the basis of ME time, search points, PSNR and Means Square Error (MSE). The algorithms evaluated in this paper are considered for state of the art video compression standards like MPEG 1, to MPEG4 and H.261 to H.264. Results show that the PSNR of Diamond Search (DS) is best for all test video sequences, whereas, Hardware Modified DS takes maximum number of search points to calculate motion vector. Moreover, hexagon search algorithm takes minimum number of search points but its PSNR is considerably lower than the other algorithms.
Unmanned Aerial Vehicle (UAV) provide bird's eye view over an intersection or a large area, and provide real-time surveillance of area under observation. UAVs have been playing a vital role in disaster management due to the increased sensing and processing capabilities. This paper proposes a fast adaptive prediction based diamond search Motion Estimation (ME) algorithm for Sun Falcon 2, a solar powered UAV's video encoder to cope the computational complexity, low power and increased quality of ME process requirement. Results show that the proposed Adaptive Predict Diamond Search (APDS) ME algorithm performs best in the term of PSNR, MSE and number of Search Points (SP), for approximately all the video sequences. Moreover, performance of APDS is decreased a little bit in term of number of SP when compared to Hexagon search algorithm but its PSNR is still considerably high for those video sequences. The average PSNR improvement rate of APDS is 0.62, 2.67, 0.82, 0.83 and 2.31 for Diamond Search (DS), HexBS, FHS, FSS and MDS respectively, while the average SIR is 25. 4404, 6.3374, 48.274 and 205.55 for DS, FHS, FSS and MDS respectively.
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