tailieunhanh - Data Mining Multimedia Soft Computin And Bioinformatics P2

In English text files, common words (., "is", "are", "the") or similar patterns of character strings (., lze\ lth\ iing'1} are usually used repeatedly. It is also observed that the characters in an English text occur in a well-documented distribution, with letter "e" and "space" being the most popular. 2. In numeric data files, often we observe runs of similar numbers or predictable interdependency amongst the numbers. 3. The neighboring pixels in a typical image are highly correlated to each other, with the pixels in a smooth region of an image having similar values. 4. Two consecutive frames in. | DATA COMPRESSION 11 1. In English text files common words . is are i ie or similar patterns of character strings . ze th ling are usually used repeatedly. It is also observed that the characters in an English text occur in a well-documented distribution with letter e and space being the most popular. 2. In numeric data files often we observe runs of similar numbers or predictable interdependency amongst the numbers. 3. The neighboring pixels in a typical image are highly correlated to each other with the pixels in a smooth region of an image having similar values. 4. Two consecutive frames in a video are often mostly identical when motion in the scene is slow. 5. Some audio data beyond the human audible frequency range are useless for all practical purposes. Data compression is the technique to reduce the redundancies in data representation in order to decrease data storage requirements and hence communication costs when transmitted through a communication network 24 25 . Reducing the storage requirement is equivalent to increasing the capacity of the storage medium. If the compressed data are properly indexed it may improve the performance of mining data in the compressed large database as well. This is particularly useful when interactivity is involved with a data mining system. Thus the development of efficient compression techniques particularly suitable for data mining will continue to be a design challenge for advanced database management systems and interactive multimedia applications. Depending upon the application criteria data compression techniques can be classified as lossless and lossy. In lossless methods we compress the data in such a way that the decompressed data can be an exact replica of the original data. Lossless compression techniques are applied to compress text numeric or character strings in a database - typically medical data etc. On the other hand there are application areas where we can compromise with the accuracy of the .

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