A novel hexagonal search algorithm for fast block matching motion estimation

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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

A Three-Point Directional Search Block Matching Algorithm

This paper proposes compact directional asymmetric search patterns, which we have named as three-point directional search (TDS). In most fast search motion estimation algorithms, a symmetric search pattern is usually set at the minimum block distortion point at each step of the search. The design of the symmetrical pattern in these algorithms relies primarily on the assumption that the direction of convergence is equally alike in each direction with respect to the search center. Therefore, the monotonic property of real-world video sequences is not properly used by these algorithms. The strategy of TDS is to keep searching for the minimum block distortion point in the most probable directions, unlike the previous fast search motion estimation algorithms where all the directions are checked. Therefore, the proposed method significantly reduces the number of search points for locating a motion vector. Compared to conventional fast algorithms, the proposed method has the fastest search speed and most satisfactory PSNR values for all test sequences

Hybrid Approach for Video Compression Using Block Matching Motion Estimation

To discard the redundancy present in video some video compression technique are involved .Basically video is a collection sequential frames in a sequence. video compression means reducing the size of video . In video sequence there are two types of technique are present that are temporal redundancy and spatial redundancy. In this paper we discuss about hybrid technique .Hybrid means combination of any two or more than two technique like efficient three step search algorithm(E3SS) and cross hexagonal search algorithm (CHS) .In today’s date block matching algorithm for motion estimation is powerful technique for high compression ratio and to reduce computational complexity .The motion estimation calculate the position of pixel and It is a custom to calculate the pixel from current frame to reference frame .The main function of motion estimation is reducing the search point and redundancy present in video .The experiment result shows that the proposal algorithm performs better than previous proposed block matching algorithms and required less computation than other technique

A Survey on Block Matching Algorithms for Video Coding

Block matching algorithm (BMA) for motion estimation (ME) is the heart to many motion-compensated video-coding techniques/standards, such as ISO MPEG-1/2/4 and ITU-T H.261/262/263/264/265, to reduce the temporal redundancy between different frames. During the last three decades, hundreds of fast block matching algorithms have been proposed. The shape and size of search patterns in motion estimation will influence more on the searching speed and quality of performance. This article provides an overview of the famous block matching algorithms and compares their computational complexity and motion prediction quality

A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

Fractal compression is the lossy compression technique in the field of gray/color image and video compression. It gives high compression ratio, better image quality with fast decoding time but improvement in encoding time is a challenge. This review paper/article presents the analysis of most significant existing approaches in the field of fractal based gray/color images and video compression, different block matching motion estimation approaches for finding out the motion vectors in a frame based on inter-frame coding and intra-frame coding i.e. individual frame coding and automata theory based coding approaches to represent an image/sequence of images. Though different review papers exist related to fractal coding, this paper is different in many sense. One can develop the new shape pattern for motion estimation and modify the existing block matching motion estimation with automata coding to explore the fractal compression technique with specific focus on reducing the encoding time and achieving better image/video reconstruction quality. This paper is useful for the beginners in the domain of video compression

Modified Three-Step Search Block Matching Motion Estimation and Weighted Finite Automata based Fractal Video Compression

The major challenge with fractal image/video coding technique is that, it requires more encoding time. Therefore, how to reduce the encoding time is the research component remains in the fractal coding. Block matching motion estimation algorithms are used, to reduce the computations performed in the process of encoding. The objective of the proposed work is to develop an approach for video coding using modified three step search (MTSS) block matching algorithm and weighted finite automata (WFA) coding with a specific focus on reducing the encoding time. The MTSS block matching algorithm are used for computing motion vectors between the two frames i.e. displacement of pixels and WFA is used for the coding as it behaves like the Fractal Coding (FC). WFA represents an image (frame or motion compensated prediction error) based on the idea of fractal that the image has self-similarity in itself. The self-similarity is sought from the symmetry of an image, so the encoding algorithm divides an image into multi-levels of quad-tree segmentations and creates an automaton from the sub-images. The proposed MTSS block matching algorithm is based on the combination of rectangular and hexagonal search pattern and compared with the existing New Three-Step Search (NTSS), Three-Step Search (TSS), and Efficient Three-Step Search (ETSS) block matching estimation algorithm. The performance of the proposed MTSS block matching algorithm is evaluated on the basis of performance evaluation parameters i.e. mean absolute difference (MAD) and average search points required per frame. Mean of absolute difference (MAD) distortion function is used as the block distortion measure (BDM). Finally, developed approaches namely, MTSS and WFA, MTSS and FC, and Plane FC (applied on every frame) are compared with each other. The experimentations are carried out on the standard uncompressed video databases, namely, akiyo, bus, mobile, suzie, traffic, football, soccer, ice etc. Developed approaches are compared on the basis of performance evaluation parameters, namely, encoding time, decoding time, compression ratio and Peak Signal to Noise Ratio (PSNR). The video compression using MTSS and WFA coding performs better than MTSS and fractal coding, and frame by frame fractal coding in terms of achieving reduced encoding time and better quality of video