An enhancement of LZW Algorithm applied in image compression and decompression | . (Record no. 25325)

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control field 76031
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control field ft6096
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control field 20251105171256.0
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fixed length control field 190131n 000 0 eng d
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Description conventions rda
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Language code of text/sound track or separate title engtag
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Classification number QA76.9 A87 2015
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Personal name Austria, Elvind Marius Y. and Veraces, Kristopher N.
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Title An enhancement of LZW Algorithm applied in image compression and decompression
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Date of production, publication, distribution, manufacture, or copyright notice c2015
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Other physical details Undergraduate Thesis: (BSCS major in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2015.
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Formatted contents note ABSTRACT: One big problem of a photographer or a person than loves photos was to how to store their images without exhausting all its disk space. Data compression is the process of reducing the size and number of bits needed to store and transmit data. This process is used to reduce the size of the file and to reduce the time needed for the transmission of data. Lempel-Ziv-Welch algorithm or also known as the LZW algorithm is a popular general algorithm used in compression and decompression. It is capable of working on almost any type of data. However, the proponents encountered the following problems with regards to the said algorithm. First is that the less the repetitive data for each pixel, the longer the compression time. For the algorithm to solve this problem, the algorithm must read 16 bits at a time for it to fasten the compression time. Second problem is that the compression and decompression of complicated image files result into a bigger file than the original. And last, there is a loss of data when it exceeds the maximum limit of the dictionary. In order to solve the stated problems, the proponents suggested the following objectives: To be able to compress colored images with the same speed as with the grayscale image. Since compression of grayscale images is much faster compare to compressing to colored images. Thus, compressing both images should have least minimum time margin or for best to compressed with same speed. Next is to improve the compression percentage of when compressing colored images or images with high color noise. And last, to be able to read multiple characters at a time and to reduce the overall size of the dictionary and to make it as small as possible and to be able to prevent loss of data. The researches recommend people to use the enhanced application, and recommend those that are interested to further enhance the system, better improving the size of the dictionary.
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Classification Filipiniana
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Institution code [OBSOLETE] lcc
Item type Thesis/Dissertation
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          Filipiniana-Thesis PLM PLM Archives Donation   QA76.9 A87 2015 FT6096 2025-09-20 Thesis/Dissertation

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