PERFORMANCE EVALUATION OF ORTHOGONAL-DIAMOND SEARCH OF BLOCK MATCHING ALGORITHM FOR VIDEO CODING

2015 ◽  
Vol 76 (1) ◽  
Author(s):  
Nurul 'Atiqah Hamid ◽  
Abdul Majid Darsono ◽  
Nurulfajar Abdul Manap ◽  
Redzuan Abdul Manap
Keyword(s):  
Signal To Noise Ratio ◽  
Video Quality ◽  
Motion Vector ◽  
Computational Cost ◽  
Block Matching ◽  
Search Pattern ◽  
Matching Algorithm ◽  
Block Matching Algorithm ◽  
Diamond Search

Several drawbacks of established fast Block Matching Algorithm (BMA) are the reasons why new fast BMAs are being developed and proposed in these recent years in order to reduce the computational cost while maintaining the quality of the video signal. In this paper, a new algorithm is proposed, namely Orthogonal-Diamond Search (ODS) which employs an orthogonal-shaped search pattern in the first step and then is switched into diamond-shaped search pattern for the next step. Few established algorithm, namely Orthogonal Search (OS), Full Search (FS), Diamond Search (DS) and Hexagon-Diamond Search (HDS) are implemented using MATLAB along with the ODS and their performance are being compared and analyzed in terms of computational complexity, peak signal-to-noise ratio (PSNR), and number of search points. Simulation result shows that the proposed algorithm can find motion vector with fewer number of search points while maintains close performance of video quality with other selected algorithms.  

A Novel Frame Rate Up-Conversion Algorithm Based on Soft Threshold Bandelet Transform

2016 ◽  
Vol 30 (07) ◽  
pp. 1650017 ◽  
Author(s):  
Mingjun Deng ◽  
Fengchun Tian ◽  
Jian Ran ◽  
Zhiyong Shi ◽  
Li Zhang
Keyword(s):  
Motion Vector ◽  
Block Matching ◽  
Frame Rate ◽  
Matching Algorithm ◽  
Block Matching Algorithm ◽  
Block Motion ◽  
Soft Threshold ◽  
Frame Rate Up Conversion ◽  
Vector Median

The most important part of frame rate up-conversion (FRUC) is block matching. The geometric properties of the image were not taken into consideration in traditional block matching algorithm, so the matching result of motion estimation cannot reach the optimal. A novel FRUC algorithm based on Bandelet was proposed in this paper. The algorithm includes: Firstly, a soft threshold Bandelet transform of matching block was performed. The optimal matching block was determined through detection of direction similarity and Bandelet coefficient similarity; secondly, vector median filtering (VMF) and overlapped block motion compensation (OBMC) were carried out by adopting motion vector to realize interpolated frame algorithm. Experimental results show that the FRUC algorithm based on Bandelet can further promote the quality of FRUC.

scholarly journals Fast Motion Estimation Algorithm using Hybrid Search Patterns for Video Streaming Application

2017 ◽  
Vol 12 (5) ◽  
pp. 715
Author(s):  
Vani Rajamanickam ◽  
Ushabhanu Nageswaran ◽  
Sangeetha Marikkannan
Keyword(s):  
Motion Estimation ◽  
Motion Vector ◽  
Block Matching ◽  
Search Pattern ◽  
Live Streaming ◽  
Hybrid Search ◽  
Fast Motion Estimation ◽  
Streaming Application ◽  
Diamond Search ◽  
Search Patterns

The objective of the paper is to develop new block matching Motion Estimation (ME) algorithm using hybrid search patterns along the direction of best match. The search efficiency for sequences with fast motions and high resolutions is improved by proposing New Cross Diagonal-Hexagon Search (NCDHS) algorithm which involves a novel multi half-hexagon grid global search pattern and a cross diagonal-hexagon local search pattern. The new search pattern enables the proposed algorithm to perform better search using 9.068 search points on an average, to obtain optimal motion vector with slight improvement in quality. This inturn reduces ME Time upto 50.11%, 47.12%, 32.99% and 43.28% on average when compared to the existing Diamond Search (DS), Hexagon Search (HS), New Cross Hexagon Search (NHEXS) and Enhanced Diamond Search (EDS) algorithms respectively. The novelty of the algorithm is further achieved by applying the algorithm proposed for live streaming application. The NCDHS algorithm is run on two MATLAB sessions on the same computer by establishing the connection using Transmission Control Protocol (TCP) /Internet Protocol (IP) network. The ME Time obtained is 14.5986 seconds for a block size 16x16, is less when compared to existing algorithms and that makes the NCDHS algorithm suitable for real time streaming application.

scholarly journals Image Forgery Detection Using Dct And Quantization Matrix Techniques

2019 ◽  
Vol 8 (6) ◽  
pp. 4575-4581
Keyword(s):  
Essential Feature ◽  
Block Matching ◽  
Forgery Detection ◽  
Discrete Cosine Transformation ◽  
Common People ◽  
Matching Algorithm ◽  
Block Matching Algorithm ◽  
Cosine Transformation ◽  
The Common

In today’s era the image has become useful for communication purpose. But due to the development of software and various techniques it is possible to change images in adding or removing essential feature from it without leaving a clue of real image. It is not easy for the common people to identify whether the image original or tampered. In order to avoid this problem, forgery detection came into existence. Detection of forgery refers to task of image processing to identify that the images are unique or tampered. Several techniques have been used in order to detect the forgeries from the forged image, but this issue has not yet solved. In order to solve these issues we have used Discrete Cosine Transformation (DCT) and quantization matrix techniques for identifying forged areas of image, where the quality of image is not reduced. The Discrete Cosine Transformation (DCT) is used in order for characterizing the overlapping blocks and quantization matrix is used to compress DCT values and gives both highly compressed and best decompressed image quality. Here we use block matching algorithm. This algorithm one of the most frequently used for detecting image which is duplicate. This proposed work also supports for different kinds of images such as JPEG, JPG or PNG of any size it can be either mxn or nxn.

scholarly journals A Survey on Block Matching Algorithms for Video Coding

2017 ◽  
Vol 7 (1) ◽  
pp. 216
Author(s):  
Adapa Venkata Paramkusam ◽  
Vuyyuru Arun
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
Block Matching ◽  
Motion Prediction ◽  
Matching Algorithm ◽  
Block Matching Algorithm ◽  
Search Patterns ◽  
Temporal Redundancy ◽  
Shape And Size

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.

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