Fast Fractal Image Encoding Algorithm Based on Coefficient of Variation Feature
In order to improve the drawback of fractal image encoding with full search typically requires a very long runtime. This paper thus proposed an effective algorithm to replace algorithm with full search, which is mainly based on newly-defined coefficient of variation feature of image block. During th...
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          | Published in | Smart Graphics Vol. 9317; pp. 175 - 183 | 
|---|---|
| Main Authors | , | 
| Format | Book Chapter | 
| Language | English | 
| Published | 
        Switzerland
          Springer International Publishing AG
    
        2017
     Springer International Publishing  | 
| Series | Lecture Notes in Computer Science | 
| Subjects | |
| Online Access | Get full text | 
| ISBN | 9783319538372 3319538373  | 
| ISSN | 0302-9743 1611-3349  | 
| DOI | 10.1007/978-3-319-53838-9_15 | 
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| Abstract | In order to improve the drawback of fractal image encoding with full search typically requires a very long runtime. This paper thus proposed an effective algorithm to replace algorithm with full search, which is mainly based on newly-defined coefficient of variation feature of image block. During the search process, the coefficient of variation feature is utilized to confine efficiently the search space to the vicinity of the domain block having the closest coefficient of variation feature to the input range block being encoded, aiming at reducing the searching scope of similarity matching to accelerate the encoding process. Simulation results of three standard test images show that the proposed scheme averagely obtain the speedup of 4.67 times or so by reducing the searching scope of best-matched block, while can obtain the little lower quality of the decoded images against the full search algorithm. Moreover, it is better than the moment of inertia algorithm. | 
    
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| AbstractList | In order to improve the drawback of fractal image encoding with full search typically requires a very long runtime. This paper thus proposed an effective algorithm to replace algorithm with full search, which is mainly based on newly-defined coefficient of variation feature of image block. During the search process, the coefficient of variation feature is utilized to confine efficiently the search space to the vicinity of the domain block having the closest coefficient of variation feature to the input range block being encoded, aiming at reducing the searching scope of similarity matching to accelerate the encoding process. Simulation results of three standard test images show that the proposed scheme averagely obtain the speedup of 4.67 times or so by reducing the searching scope of best-matched block, while can obtain the little lower quality of the decoded images against the full search algorithm. Moreover, it is better than the moment of inertia algorithm. | 
    
| Author | Li, Shan-shan Li, Gao-ping  | 
    
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| Copyright | Springer International Publishing AG 2017 | 
    
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| DOI | 10.1007/978-3-319-53838-9_15 | 
    
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| Discipline | Computer Science | 
    
| EISBN | 3319538381 9783319538389  | 
    
| EISSN | 1611-3349 | 
    
| Editor | Chen, Yaxi Tan, Wenrong Christie, Marc  | 
    
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| EndPage | 183 | 
    
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| Notes | G. Li—Fund Project: Supported by Application Foundation Projects in Sichuan province (No. 2013JY0180), and Supported by Foundation of Sichuan Educational Committee (No. 15ZA0384), and Supported by Foundation of Southwest University for Nationalities (No. 2012NYT001). | 
    
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| PublicationSeriesSubtitle | Image Processing, Computer Vision, Pattern Recognition, and Graphics | 
    
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| PublicationSubtitle | 13th International Symposium, SG 2015, Chengdu, China, August 26-28, 2015, Revised Selected Papers | 
    
| PublicationTitle | Smart Graphics | 
    
| PublicationYear | 2017 | 
    
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| RelatedPersons | Kleinberg, Jon M. Mattern, Friedemann Naor, Moni Mitchell, John C. Terzopoulos, Demetri Steffen, Bernhard Pandu Rangan, C. Kanade, Takeo Kittler, Josef Weikum, Gerhard Hutchison, David Tygar, Doug  | 
    
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| Snippet | In order to improve the drawback of fractal image encoding with full search typically requires a very long runtime. This paper thus proposed an effective... | 
    
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| StartPage | 175 | 
    
| SubjectTerms | Coefficient of variation feature Fractal Fractal image coding Image compression  | 
    
| Title | Fast Fractal Image Encoding Algorithm Based on Coefficient of Variation Feature | 
    
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