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Comparison and Analysis of an efficient Image Compression Technique Based on Discrete 2-D wavelet transforms with Arithmetic Coding

Author(s): Deepika Sunoriya | Prof. Uday Pratap Singh | Prof. Vineet Ricchariya

Journal: International Journal of Advanced Computer Research
ISSN 2249-7277

Volume: 2;
Issue: 5;
Start page: 65;
Date: 2012;
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Keywords: Walsh-Wavelet Transform | Image Compression | db1 | db2 | Quantization

When a great deal is known about the regularitiesin the files to be compressed, e.g., in thecompression of image, audio, photo and video data,it is possible to match different compressionalgorithms with different parts of the data in such away to achieve the maximum compression ratio,thereby providing significant reductions in file sizes.These algorithms are difficult to derive and areoften the result of many person years of effort.Nonetheless, these are so successful that effectivelysome types of data are regularly saved, kept andtransferred, only in compressed form, to bedecompressed automatically and transparently tothe user only when loaded into applications thatmake use of them. Our proposed approach is thecombination of several approaches to make thecompression better than the previous usedapproach. We first apply two Levels DiscreteWavelet Transform and then apply Walsh-WaveletTransform on each 8x8 block of the low-frequencysub-band, then Split all DC values form eachtransformed block 8x8. Finally we performcompression by using arithmetic coding. In ouralgorithm we provide the basis of accepting imagesfrom the database. We concentrate the type of thewavelet we use like db1, db2, db3 etc. Then we usethe quantization factor which is CF1 and CF2 inour case. We use the value as 0.05 and 0.2 as thequantization factor. After matlab simulation we canfind our results suitable than the previous work.
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