文章基本信息

标题：Compression – Innovated Using Wavelets in Image
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作者：P.KAVITHA
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2013
卷号：1
期号：2
出版社：S&S Publications
摘要：In this technological field, image storage is happening through the personal computer. A medical doctor can makea diagnosis using a full three – dimensional image on a computer screen – not long ago surgery would have been necessary tocapture the same critical point of view. Satellite images of earth and places beyond is been continually transmitted overcommunication channels. The Internet – still in its childhood – continues to flourish and influence our personal and professionallives. Common to these and many other applications is the storage of digital imagery. The proliferation of digital media hasmotivated innovative methods for compressing digital images. The popular Joint Photographic Experts Group (JPEG) andGraphical Interchange Format (GIF) standards have been the prevailing methodologies in image compression in the pastdecade. Alternatively, recent research in digital image compression has explored and improved the utility of the wavelettransform; its success as a compression technique has prompted its inclusion in the JPEG 2000 standard. This study has threemain objectives.1. To ‘compress’ an image by taking it’s wavelet representation and throwing out those coefficients whoseweight was lower than some fraction of the norm.2. To use the wavelets belong to the Deslauriers- Dubuc family.3. To workwith a specific kind of thresholding and basis functions for compression.The applications of many wavelet based compressionschemes most widely used Daubechies wavelet family, which are symmetric biorthogonal wavelets. However, this thesissignificantly presents Deslauriers - Dubuc family set of wavelets, which is also symmetric biorthogonal for the transformationof the image.The steps involved to compress an image in this paper are as follows:1. Digitize the source image into a signal s, which is a string of numbers.2. Decompose the signal into a sequence of wavelet coefficients W.3. Use threshold to modify the wavelet coefficients from w to another sequence W’.4. Use quantization to convert W’ to a sequence q.5. Apply entropy coding to compress q into a sequence e.
关键词：Wavelet; Daubechies; Deslauriers-Dubu; Threshold; Joint Photographic Experts Group (JPEG); Discrete;wavelet transform (DWT)