基于改进Lempel-Ziv-Welch算法的孟加拉文文本压缩

Linkon Barua, P. K. Dhar, Lamia Alam, I. Echizen
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引用次数: 14

摘要

文本压缩算法在字符级别执行压缩。孟加拉语文本有一些独特的特点,如没有明显的大小写字母,辅音集群(CC)和辅音依赖元音符号(CV)等。传统的Lempel-Ziv-Welch (LZW)算法不适合压缩带状文本。因此,本文提出了一种改进的LZW (MLZW)算法,可以有效地压缩孟加拉语文本。在我们建议的方法中,使用Unicode范围为1-90的字典来存储孟加拉字符。压缩过程从检查输入字符开始。如果输入字符是CC或CV的一部分,则将CC或CV视为字符并在字典中搜索。如果要编码的字符已经在字典中,则使用字典索引对其进行编码。否则,该字符将被添加到字典中,并使用其相应的字典索引进行编码。仿真结果表明,所提出的MLZW算法能够有效地压缩孟加拉语文本。我们观察到,与LZW算法相比,所提出的MLZW算法对字典索引的压缩率约为3%,对输出序列的压缩率约为33%。
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Bangla text compression based on modified Lempel-Ziv-Welch algorithm
Text compression algorithm performs compression at the character level. Bangla text has some unique features such as no distinct upper and lower case letter, consonant cluster (CC) and consonant with dependent vowel sign (CV) etc. The conventional Lempel-Ziv-Welch (LZW) algorithm is not suitable for compressing Bangle text. Therefore, in this paper, we propose a modified LZW (MLZW) algorithm which can compress Bangla text effectively and efficiently. In our proposed method, a dictionary with Unicode ranges from 1–90 is used for Bangla characters. The compression process is started with checking the input character. If input character is a part of CC or CV, then CC or CV is considered as a character and search it in the dictionary. If the character to be encoded is already in dictionary, encode it with the dictionary index. Otherwise, the character is added to the dictionary and is encoded with its corresponding dictionary index. Simulation results indicate that the proposed MLZW algorithm compresses Bangla text effectively and efficiently. We observed that the proposed MLZW provides higher compression rate approximately 3% for dictionary index and 33% for output sequence compared with LZW algorithm.
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