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Copyright © 2015
M. S. Thirumalai
Publisher: M.S. Thirumalai
11249 Oregon Circle
Bloomington, MN 55438
Amended Golomb Coding (AGC) Implementation for
Saranya G., M.E.
Loganya R., M.E. Student
An efficient lossless compression technique to reduce the configuration time of reconfigurable devices known as AGC (AMENDED GOLOMB CODING) is proposed. The time for loading of the configuration data from outside the chip often bottlenecks the system performance for some dynamically reconfigurable applications. Reducing the amount of configuration data with compression technique is one of the efficient approaches to improve the configuration speed. In this paper existing lossless compression technique known as Golomb Codes is amended so that compression efficiency for reconfigurable devices is still enhanced. In AGC the codeword is generated by appending the optimal prefix (amending the original Golomb’s prefix), hole bit and tail in such a way that compression efficiency is enhanced.
Keywords: AGC, Compression Efficiency, Golomb codes, Lossless compression, optimal prefix.
Compression is a way of reducing the original bits required to transfer the source of information while preserving the original content at the decompression side for the purpose of effective transmission and enhancing the storage capacity. Compression reduces the amount of data storage space and data transmission time. Compression is performed by a program that uses a formula or algorithm to determine how to shrink the size of the data. The same program can be used at the receiver side for decompression .Text compression can be as simple as removing all unneeded characters, inserting a single repeat character to indicate a string of repeated characters, and substituting a smaller bit string for a frequently occurring bit string. Compression can be performed on the data content or on the entire transmission unit, including header data. Data compression is usually of two types: lossy and lossless . Lossless compression is a class of data compression algorithms that allows the original data to be perfectly reconstructed from the compressed data. Lossless compression algorithms reduce file size with no loss in image quality. The original data is retrieved as it is at the decompression stage. This is because file is only “temporally thrown away” and not discarded hence we could read the original data without loss of information. While the advantage of this is that it maintains quality the main disadvantage is it doesn't reduce the file size as much as lossy compression. Lossy compression permits reconstruction only of an approximation of the original data, though this usually improves compression rates (and therefore reduces file sizes). Lossy compression also looks for 'redundant' pixel information, however, it permanently discards it. This means that when the file is decompressed the original data isn't retrieved. Lossy compression isn't used for data. Lossy is only effective with media elements that can still 'work' without all their original data. The Golomb code can be applied, if numbers of unknown size to be saved, but the actual application is in data compression .Golomb code can similarly efficient as the Huffman code  to be, but is more economical in the sense it occupies less memory, and is easier to implement and faster in execution. The proposed AGC is still effective since it enhances the compression achieved by GOLOMB and it could be compared with previous lossless compression .
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Loganya R., M.E. Student
Department of Electronics & Communication Engineering
Sri Subramanya College of Engineering & Technology
NH - 209, Sukkamanaickenpatti