Performance Analysis of Hexagon-Diamond Search Algorithm for Motion Estimation

Manap, Redzuan Abdul; Ranjit, S. S. S.; Basari, Amat Amir; Ahmad, B. H.

doi:10.1109/iccet.2010.5485814

Cited by 18 publications

(10 citation statements)

References 11 publications

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“…By calculating motion vectors this motion estimation can be done. [11], [12], [14]. Figure 1 shows block diagram of the basics of modern video compression process using motion estimation.…”

confidence: 99%

Hybrid approach for video compression based on scene change detection

Chauhan

Parmar²,

Parmar³

et al. 2013

2013 IEEE International Conference on Signal Processing, Computing and Control (ISPCC)

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In order to fulfill the requirement of limited channel bandwidth and of growing video demand like streaming media delivery on internet, and digital library, video compression is necessary. In video compression, temporal redundancy between adjacent frames is removed with block based motion estimation algorithms. Video represents a sequence of frames captured from camera. Scene is a series of consecutive frames captured from narrative point of view. In this paper we present an effective scene change detection method for an uncompressed video. We have divided frames in to blocks and applied a canny edge detector in consecutive frames. Count no of pixels (ones) in each block and compare it with consecutive frames. If scene change happens then number of pixels per block will change, based on that change we can detect scene change in consecutive frame. Here we have presented a hybrid approach, in which we have used scene change detection along with block based motion estimation algorithms (BME) to compress video.

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“…By calculating motion vectors this motion estimation can be done. [11], [12], [14]. Figure 1 shows block diagram of the basics of modern video compression process using motion estimation.…”

confidence: 99%

Hybrid approach for video compression based on scene change detection

Chauhan

Parmar²,

Parmar³

et al. 2013

2013 IEEE International Conference on Signal Processing, Computing and Control (ISPCC)

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“…It is observed that the size and shape of any search pattern can increase or decrease the search speed and the quality of a video considerably [2][3][4][5][6][7].…”

Section: Search Pattern and Me Accuracy Analysismentioning

confidence: 99%

“…Furthermore, the continuing search procedure keeps finding the best matching point, hence reduces the distortion measure by avoiding the search trap in local minimas. The hexagon search pattern elaborated in [6] has a circular type shape which covers the large area as compared to DS but has to total seven, reduced number of search points. Due to the reduced number search points, HexBS ME algorithm has greater search speed than the DS algorithm.…”

Section: Search Pattern and Me Accuracy Analysismentioning

confidence: 99%

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Adaptive Prediction based Diamond Search Algorithm (APDS) for Video Encoder of Solar Powered UAV

Khokhar¹,

Harasani²

2016

IJCA

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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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“…This cost function is based on a Minimum Block Distortion (MBD). The cost function may be the SAD or Mean Absolute Differences (MAD) and Mean Squared Error (MSE) [7,8]. All these cost functions are given in the following equations respectively.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Fast Block Matching Motion Estimation Algorithms

Khokhar¹,

Harasani²

2015

IJCA

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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.

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Performance Analysis of Hexagon-Diamond Search Algorithm for Motion Estimation

Cited by 18 publications

References 11 publications

Hybrid approach for video compression based on scene change detection

Hybrid approach for video compression based on scene change detection

Adaptive Prediction based Diamond Search Algorithm (APDS) for Video Encoder of Solar Powered UAV

Performance Analysis of Fast Block Matching Motion Estimation Algorithms

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