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Lossless Im.ge Com.ression Technique Using Com.ination m.thods

Journal of Software Engineering and Applications 2012年第10期5卷 752-763页

作者： A. Alarabeyyat S. Al-Hashem. T. Khdour m. hjouj btoush S. Bani-Ahm.d R. Al-Hashem. S. Bani-Ahm.d Prince Abdulah Bin Gazi Faculty of Inform.tion Technology Al-Balqa Applied University Salt Jordan The Com.uter Inform.tion System. departm.nt College of Information Technology Al-Hussein Bin Talal University

The developm.nt of m.ltim.dia and digital im.ging has led to high quantity of data required to represent m.dern im.gery. This requires large disk space for storage, and long tim. for transm.ssion over com.uter networks, and these two are relatively expensive. These factors prove the need for im.ges com.ression. Im.ge com.ression addresses the problem.of reducing the am.unt of space required to represent a digital im.ge yielding a com.act representation of an im.ge, and thereby reducing the im.ge storage/transm.ssion tim. requirem.nts. The key idea here is to rem.ve redundancy of data presented within an im.ge to reduce its size without affecting the essential inform.tion of it. We are concerned with lossless im.ge com.ression in this paper. Our proposed approach is a m.x of a num.er of already existing techniques. Our approach works as follows: first, we apply the well-known Lem.el-Ziv-Welch (LZW) algorithm.on the im.ge in hand. What com.s out of the first step is forward to the second step where the Bose, Chaudhuri and Hocquenghem.(BCH) error correction and detected algorithm.is used. To im.rove the com.ression ratio, the proposed approach applies the BCH algorithm. repeatedly until “inflation” is detected. The experim.ntal results show that the proposed algorithm.could achieve an excellent com.ression ratio without losing data when com.ared to the standard com.ression algorithm..

关键词： Im.ge Com.ression LZW BCH

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A Com.lexity Analysis and Entropy for Different Data Com.ression Algorithm. on Text Files

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Journal of Com.uter and Com.unications 2018年第1期6卷 301-315页

作者： m.ham.ad hjouj btoush Ziad E. Dawahdeh Departm.nt of Com.uter Science Al-Balqa Applied University Mutah University Karak Jordan

In this paper, we analyze the com.lexity and entropy of different m.thods of data com.ression algorithm.: LZW, Huffm.n, Fixed-length code (FLC), and Huffm.n after using Fixed-length code (HFLC). We test those algorithm. on different files of different sizes and then conclude that: LZW is the best one in all com.ression scales that we tested especially on the large files, then Huffm.n, HFLC, and FLC, respectively. Data com.ression still is an im.ortant topic for research these days, and has m.ny applications and uses needed. Therefore, we suggest continuing searching in this field and trying to com.ine two techniques in order to reach a best one, or use another source m.pping (Ham.ing) like em.edding a linear array into a Hypercube with other good techniques like Huffm.n and trying to reach good results.

关键词： Text Files Data Com.ression Huffm.n Coding LZW Ham.ing Entropy Com.lexity

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