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標題: An Image Compression Method Based on Multiple Models for the Probabilities of Patterns
作者: Chan, Y.K.
Wang, C.L.
關鍵字: lossless compressing;statistical model based compressing;arithmetic;coding;base switching transformation
Project: International Journal of Imaging Systems and Technology
期刊/報告no:: International Journal of Imaging Systems and Technology, Volume 19, Issue 4, Page(s) 362-368.
This article proposes an image compression method based on multiple models for the probabilities of patterns (MMPP method) to encode a gray-level image f. First, the MMPP method employs a median edge detector (MED) to reduce the entropy of f. The intensities of two adjacent pixels in an image are usually close to each other. A base switching transformation (BST) is then used to lessen the spatial redundancy of f. Finally, the arithmetic encoding method is applied to further encode the data generated after the processing of MED and BST To reduce the memory space required to hold f, the MMPP method classifies the data and then compresses the data in each cluster by the arithmetic encoding method based on different probability tables. The experimental results show that mostly the MMPP method can provide better efficiency in memory space than the lossless JPEG 2000 method does. (C) 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 362-368, 2009; Published online in Wiley InterScience ( DOI 10.1002/ima.20214
ISSN: 0899-9457
DOI: 10.1002/ima.20214
Appears in Collections:資訊管理學系

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