Semi-hierarchical based motion estimation algorithm for the dirac video encoder

Having fast and efficient motion estimation is crucial in today’s advance video compression technique since it determines the compression efficiency and the complexity of a video encoder. In this paper, a method which we call semi-hierarchical motion estimation is proposed for the Dirac video encoder. By considering the fully hierarchical motion estimation only for a certain type of inter frame encoding, complexity of the motion estimation can be greatly reduced while maintaining the desirable accuracy. The experimental results show that the proposed algorithm gives two to three times reduction in terms of the number of SAD calculation compared with existing motion estimation algorithm of Dirac for the same motion estimation accuracy, compression efficiency and PSNR performance. Moreover, depending upon the complexity of the test sequence, the proposed algorithm has the ability to increase or decrease the search range in order to maintain the accuracy of the motion estimation to a certain level

Dynamically variable step search motion estimation algorithm and a dynamically reconfigurable hardware for its implementation

Motion Estimation (ME) is the most computationally intensive part of video compression and video enhancement systems. For the recently available High Definition (HD) video formats, the computational complexity of De full search (FS) ME algorithm is prohibitively high, whereas the PSNR obtained by fast search ME algorithms is low. Therefore, ill this paper, we present Dynamically Variable Step Search (DVSS) ME algorithm for Processing high definition video formats and a dynamically reconfigurable hardware efficiently implementing DVSS algorithm. The architecture for efficiently implementing DVSS algorithm. The simulation results showed that DVSS algorithm performs very close to FS algorithm by searching much fewer search locations than FS algorithm and it outperforms successful past search ME algorithms by searching more search locations than these algorithms. The proposed hardware is implemented in VHDL and is capable, of processing high definition video formats in real time. Therefore, it can be used in consumer electronics products for video compression, frame rate up-conversion and de-interlacing(1)

An Investigation of Block Searching Algorithms for Video Frame Codecs

Block matching is the most computationally demanding aspect of the video encoding process. In many applications real-time video encoding is desired and therefore it is important that the encoding is fast. Also where handheld devices such as a PDA or mobile phone are concerned a less computationally intensive algorithm means a simpler processor can be used which saves on hardware costs and also extends battery life. An optimised algorithm also allows these devices to be used in low bandwidth wireless networks. The challenge is to decrease the computational load on the system without compromising the quality of the video stream too much, thus enabling easier and less expensive implementations of real-time encoding. This thesis appraises some of the principal Block Search Algorithms used in Video compression today. This work follows on from the work of Aroh Barjatya who implemented 7 common Block Search Algorithms to predict P-frames in MATLAB. Three further hybrid DS algorithms are implemented in MATLAB. Additional code is added to produce plots of the main metrics and to calculate some statistics such as Average Searching Points, Average PSNR and the Speed Improvement Ratio with respect to the Diamond Search and the Exhaustive Search. For a comparative analysis with previous studies 3 standard industry test sequences are used. The first sequence, Miss America is a typical videoconferencing scene with limited object motion and a stationary background. The second sequence, Flower Garden consists mainly of stationary objects, but with a fast camera panning motion. The third sequence, Football contains large local object motion. The performance of the 3 implemented algorithms were assessed by the aforementioned statistics. Simulation results showed that the NCDS was the fastest algorithm amongst the 3 hybrid DS algorithms simulated. A speedup ranging from 10% for the complex motion sequence Flower Garden to nearly 54% for the low motion video conferencing sequence Miss America was recorded. All 3 algorithms performed very competitively in terms of PSNR compared to the DS even though they use a lower number of search points on average. It was shown that the NCDS has marginally worse PSNR performance than the DS compared to the other 2 algorithms – the highest being a drop in PSNR of 0.680dB for the Flower Garden sequence. However, the speed improvements for NCDS are quite substantial and thus would justify its use over the DS. The results from the implementation concurred with the literature therefore validating the implementation. The implementation was used as a guide in nominating a ‘robust’ Block Search Algorithm. When the DS, CDS, SCDS and the NCDS were compared with ARPS it was shown that ARPS generally gave both higher PSNR and higher search speed for all 3 sequences. The reason for the good performance of ARPS is that it quickly directs the search into the local region of the global minimum by calculating the Predicted Motion Vector. The minimum error from a rood pattern of nodes is found and then a final refined search calculates the motion vector. Simulation results showed that ARPS was the best algorithm amongst the 10 algorithms simulated from the point of view of speed (lowest number of search points used per macroblock) and video quality (PSNR). For real-time encoding of video the best fast block motion algorithm to advise is ARPS

A Novel Hybrid Approach for Fast Block Based Motion Estimation

The current work presents a novel hybrid approach for motion estimation of various video sequences with a purpose to speed up the entire process without affecting the accuracy. The method integrates the dynamic Zero motion pre-judgment (ZMP) technique with Initial search centers (ISC) along with half way search termination and Small diamond search pattern. Calculation of the initial search centers has been shifted after the process of zero motion pre-judgment unlike most the previous approaches so that the search centers for stationary blocks need not be identified. Proper identification of ISC dismisses the need to use any fast block matching algorithm (BMA) to find the motion vectors (MV), rather a fixed search pattern such as small diamond search pattern is sufficient to use. Half way search termination has also been incorporated into the algorithm which helps in deciding whether the predicted ISC is the actual MV or not which further reduced the number of computations. Simulation results of the complete hybrid approach have been compared to other standard methods in the field. The method presented in the manuscript ensures better video quality with fewer computations

A Review Paper On Motion Estimation Techniques

Motion estimation (ME) is a primary action for video compression. Actually, it leads to heavily to the compression efficiency by eliminating temporal redundancies. This approach is one among the critical part in a video encoder and can take itself greater than half of the coding complexity or computational coding time. Several fast ME algorithms were proposed as well as realized. In this paper, we offers a brief review on various motion estimation techniques mainly block matching motion estimation techniques. The paper additionally presents a very brief introduction to the whole flow of video motion vector calculation

Motion estimation with chessboard pattern prediction strategy

Due to high correlations among the adjacent blocks, several algorithms utilize movement information of spatially and temporally correlated neighboring blocks to adapt their search patterns to that information. In this paper, this information is used to define a dynamic search pattern. Each frame is divided into two sets, black and white blocks, like a chessboard pattern and a different search pattern, is defined for each set. The advantage of this definition is that the number of spatially neighboring blocks is increased for each current block and it leads to a better prediction for each block. Simulation results show that the proposed algorithm is closer to the Full-Search algorithm in terms of quality metrics such as PSNR than the other state-of-the-art algorithms while at the same time the average number of search points is less.info:eu-repo/semantics/publishedVersio

An improved block matching algorithm for motion estimation invideo sequences and application in robotics

Block Matching is one of the most efficient techniques for motion estimation for video sequences. Metaheuristic algorithms have been used effectively for motion estimation. In this paper, we propose two hybrid algorithms: Artificial Bee Colony with Differential Evolution and Harmony Search with Differential Evolution based motion estimation algorithms. Extensive experiments are conducted using four standard video sequences. The video sequences utilized for experimentation have all essential features such as different formats, resolutions and number of frames which are generally required in input video sequences. We compare the performance of the proposed algorithms with other algorithms considering various parameters such as Structural Similarity, Peak Signal to Noise Ratio, Average Number of Search Points etc. The comparative results demonstrate that the proposed algorithms outperformed other algorithms

Precise foreground detection algorithm using motion estimation, minima and maxima inside the foreground object

In this paper the precise foreground mask is obtained in a complex environment by applying simple and effective methods on a video sequence consisting of multi-colour and multiple foreground object environment. To detect moving objects we use a simple algorithm based on block-based motion estimation, which requires less computational time. To obtain a full and improved mask of the moving object, we use an opening-and-closing-by- reconstruction mechanism to identify the minima and maxima inside the foreground object by applying a set of morphological operations. This further enhances the outlines of foreground objects at various stages of image processing. Therefore, the algorithm does not require the knowledge of the background image. That is why it can be used in real world video sequences to detect the foreground in cases where we do not have a background model in advance. The comparative performance results demonstrate the effectiveness of the proposed algorithm.The Institute of Management Sciences Peshawar (http://imsciences.edu.pk/) through Higher Education Commission Islamabad, Pakistan (http://hec.gov.pk/)

An improved block matching algorithm for motion estimation in video sequences and application in robotics

Block Matching is one of the most efficient techniques for motion estimation for video sequences. Metaheuristic algorithms have been used effectively for motion estimation. In this paper, we propose two hybrid algorithms: Artificial Bee Colony with Differential Evolution and Harmony Search with Differential Evolution based motion estimation algorithms. Extensive experiments are conducted using four standard video sequences. The video sequences utilized for experimentation have all essential features such as different formats, resolutions and number of frames which are generally required in input video sequences. We compare the performance of the proposed algorithms with other algorithms considering various parameters such as Structural Similarity, Peak Signal to Noise Ratio, Average Number of Search Points etc. The comparative results demonstrate that the proposed algorithms outperformed other algorithms