Lossless computational reduction of full search algorithm in motion estimation using appropriate matching unit from image localization

Block motion estimation using full search is computationally intensive. Previously proposed fast algorithms reduce computation by limiting the number of search locations and search directions in a predefined search region. This is accomplished at the expense of accuracy of motion estimation and a large mean squared error for motion-compensated images, especially for image sequences with large displacement and rotation. In this paper, a novel efficient search algorithm for block motion estimation is presented to produce better performance than some fast search algorithms that have been developed, such as three step search, orthogonal search, 2D-logarithmic search, four step search, and block-based gradient descent search, in large displacement and rotation image cases. The proposed algorithm is based on the notion of locally multi-scale operation, search of global minimum, and two layer search strategy. Experimental results show that the proposed algorithm produces anticipative performance while costing much less computation power than the full search algorithm.

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A Memory Hierarchy Model Based on Data Reuse for Full-Search Motion Estimation on High-Definition Digital Videos

International Journal of Reconfigurable Computing ◽

10.1155/2012/473725 ◽

2012 ◽

Vol 2012 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Alba Sandyra Bezerra Lopes ◽

Ivan Saraiva Silva ◽

Luciano Volcan Agostini

Keyword(s):

Motion Estimation ◽

Search Algorithm ◽

Memory Hierarchy ◽

Block Size ◽

Data Reuse ◽

External Memory ◽

Memory Bandwidth ◽

High Definition ◽

Hierarchy Model ◽

Full Search

The motion estimation is the most complex module in a video encoder requiring a high processing throughput and high memory bandwidth, mainly when the focus is high-definition videos. The throughput problem can be solved increasing the parallelism in the internal operations. The external memory bandwidth may be reduced using a memory hierarchy. This work presents a memory hierarchy model for a full-search motion estimation core. The proposed memory hierarchy model is based on a data reuse scheme considering the full search algorithm features. The proposed memory hierarchy expressively reduces the external memory bandwidth required for the motion estimation process, and it provides a very high data throughput for the ME core. This throughput is necessary to achieve real time when processing high-definition videos. When considering the worst bandwidth scenario, this memory hierarchy is able to reduce the external memory bandwidth in 578 times. A case study for the proposed hierarchy, using32×32search window and8×8block size, was implemented and prototyped on a Virtex 4 FPGA. The results show that it is possible to reach 38 frames per second when processing full HD frames (1920×1080pixels) using nearly 299 Mbytes per second of external memory bandwidth.

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Block Based Motion Estimation Algorithms: Analysis

International Journal of Computers ◽

10.46300/9108.2020.14.2 ◽

2020 ◽

Vol 14 ◽

Keyword(s):

Motion Estimation ◽

Video Coding ◽

Video Processing ◽

Search Algorithm ◽

Video Sequences ◽

Estimation Process ◽

Estimation Algorithms ◽

Block Based ◽

Temporal Redundancy ◽

Full Search

several video coding standards and techniques have been introduced for multimedia applications, particularly h.26x series for video processing. These standards employ motion estimation process in order to reduce the amount of data that is required to store or transmit the video. Motion estimation process is an inextricable part of the video coding as it removes the temporal redundancy between successive frames of video sequences. This paper is about these motion estimation algorithms, their search procedures, complexity, advantages, and limitations. A survey of motion estimation algorithms including full search algorithm, many fast search and fast full search block based algorithms has been presented. An evaluation of up to date motion estimation algorithms, based on a number of empirical results on several test video sequences, is presented as well.

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