JOURNAL ARTICLE

<title>Fast classification method for fractal image compression</title>

Trieu‐Kien TruongJyh H. Jeng

Year: 2000 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 4122 Pages: 190-193   Publisher: SPIE

Abstract

In this paper, a fast algorithm is developed which reduces the searching space for Fractal image coding. The basic idea is to classify the domain pool into three classes, non- edged class, horizontal/vertical class and the diagonal class. For each given range block, the property is computed first to determine which class it belongs. Then one only has to search from the corresponding class in the domain pool to find the best match. The classification operation is performed only according to the lowest frequency coefficients of the given block in the horizontal and vertical directions, in which the frequency data is computed from Discrete Cosine Transform (DCT). The main advantages for this classification scheme are that the classification mechanism is simple and the DCT algorithm is easy to implement. A simulation shows that, the proposed fast algorithm is about 2 times faster than the baseline method while the quality of the retrieved image is almost the same.

Keywords:
Discrete cosine transform Computer science Diagonal Fractal compression Fractal Algorithm Block (permutation group theory) Image (mathematics) Coding (social sciences) Artificial intelligence Frequency domain Class (philosophy) Contextual image classification Data compression Pattern recognition (psychology) Property (philosophy) Image compression Computer vision Image processing Mathematics

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Topics

Mathematical Dynamics and Fractals
Physical Sciences →  Mathematics →  Mathematical Physics
Neural Networks and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence
Chaos-based Image/Signal Encryption
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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