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在图像中使用小波进行创新压缩

摘要

在这个技术领域，图像存储是通过个人电脑实现的。医生可以在电脑屏幕上使用完整的三维图像进行诊断——不久以前，为了获得同样的关键观点，手术是必要的。地球和其他地方的卫星图像通过通信渠道不断传输。互联网——仍处于童年时期——继续蓬勃发展，并影响着我们的个人和职业生活。这些和许多其他应用的共同之处是数字图像的存储。数字媒体的普及催生了压缩数字图像的创新方法。在过去的十年中，流行的联合摄影专家组(JPEG)和图形交换格式(GIF)标准一直是图像压缩的主流方法。另外，最近在数字图像压缩方面的研究已经探索和改进了小波变换的实用性;它作为一种压缩技术的成功促使它被纳入jpeg2000标准。本研究有三个主要目标。 To ‘compress’ an image by taking it’s wavelet representation and throwing out those coefficients whose weight was lower than some fraction of the norm.2. To use the wavelets belong to the Deslauriers- Dubuc family.3. To work with a specific kind of thresholding and basis functions for compression.The applications of many wavelet based compression schemes most widely used Daubechies wavelet family, which are symmetric biorthogonal wavelets. However, this thesis significantly presents Deslauriers - Dubuc family set of wavelets, which is also symmetric biorthogonal for the transformation of 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.

P.Kavitha

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