Implementation Of New Three Step Search Algorithm For Motion Estimation Using MATLAB
To achieve high compression ratio in video coding, a technique known as Block Matching Motion Estimation has been widely adopted in various coding standards. This technique is implemented conventionally by exhaustively testing all the candidate blocks within the search window .This type of implement...
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| Format: | Monograph |
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UTeM
2010
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| Online Access: | http://library.utem.edu.my:8000/elmu/index.jsp?module=webopac-d&action=graphicFullDisplayRetriever.jsp&szMaterialNo=0000062951 http://library.utem.edu.my:8000/elmu/index.jsp?module=webopac-d&action=graphicFullDisplayRetriever.jsp&szMaterialNo=0000062951 http://eprints.utem.edu.my/4764/1/Implementation_Of_New_Three_Step_Search_Algorithm_For_Motion_Estimation_Using_MATLAB_-_24_pages.pdf http://eprints.utem.edu.my/4764/2/Implementation_Of_New_Three_Step_Search_Algorithm_For_Motion_Estimation_Using_MATLAB_-_Full_Text.pdf |
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| Summary: | To achieve high compression ratio in video coding, a technique known as Block Matching Motion Estimation has been widely adopted in various coding standards. This technique is implemented conventionally by exhaustively testing all the candidate blocks within the search window .This type of implementation, called Full Search (FS) Algorithm, gives the optimum solution. However, substantial amount of computational workload is required in this algorithm. To overcome this drawback, many fast Block Matching Algorithms (BMAs) have been proposed and developed. Different search patterns and strategies are exploited in these algorithms in order to find the optimum motion vector with minimal number of required search points. One of these fast BMAs, which is proposed to be implemented in this project, is called New Three Step Search (NTSS) Algorithm. This project requires the algorithm to be implemented in MATLAB and then its performance is compared to FS algorithm as well as to other fast BMAs in terms of the peak signal-to-noise ratio (PSNR), number of required search points and computational complexity. |
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