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Image compression using wavelets
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小波变换源码，国外VC开发的，效果比较好
I ve been involved with wavelet-analysis since my Ph.D studies and over the years developed various wavelet-transforms C++ libraries. This one concerns 2D implementation of the Fast wavelet transform (FWT). The 2D FWT is used i
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基于小波变换的图像压缩编码，实现了多种小波变换，并且实现了12:1的高压缩率。-Based on Wavelet Transform Image Coding, to achieve a variety of wavelet transform, and achieved a high 12:1 compression ratio.
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用matlab编写的程序集合，主要是完成括亮度变换、线性和非线性空间滤波、图像复原与配准、彩色图像处理、小波、图像数据压缩、形态学图像处理、识别-Matlab procedures used to prepare the collection, mainly including brightness achieve transformation, linear and nonlinear spatial filtering, image restoration and registration,
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image compression using wavelets
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hi this the code for image compression using different transoformation coding algorithms in wavelets,that is all wavelets-hi this is the code for image compression using different transoformation coding algorithms in wavelets,that is all wavelets
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The following implementation steps have been made for the devised algorithm, which is based on 2D-wavelet.
1. Reading an image of either gray scale or RGB image.
2. Converting the image into grayscale if the image is RGB.
3. Decomposition of im
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主要用于图像经小波变换压缩图像，并计算压缩后的图像压缩性能即压缩比和信噪比-Mainly used for image compression by wavelet transform image, and calculate the compressed image compression performance that the compression ratio and signal to noise ratio
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在实数域 ,对称、 正交的紧支集非平凡单小波基不存在 ,而多小波把紧支集，对称性、 正交性完美地结合在一起 ,使小波理论从标量扩展到矢量范畴。利用上述特点将多小波变换应用于 SAR 图像压缩。-In the real fields, symmetric, orthogonal set of nontrivial compactly supported wavelet basis does not exist alone, but more than the compact support wav
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原书《小波十讲》（TenLecturesonWavelets）是一本世界范围公认的经典学术名著，是当代数学著作中一本影响巨大的绝妙好书。书中包含了20世纪80年代以来世界上有关小波分析的最先进成果，也包含Daubechies本人关于紧支撑小波的卓越成就。对于学习研究小波理论、探讨分析小波应用的人而言，此书是不可不读的基础性经典著作。-The original book " Ten Lectures on Wavelets" (TenLecturesonWavelets) is
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This paper presents a new coding technique based on
contourlet transform and multistage vector
quantization. Wavelet based Algorithms for image
compression results in high compression ratios
compared to other compression techniques. Wavelets
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本书在介绍MATLAB编程基础知识之后，主要围绕数字图像处理的主干内容展开。这些内容包括：亮度变换、线性和非线性空间滤波、频率域滤波、图像复原与配准、彩色图像处理、小波、图像数据压缩、形态学图像处理、图像分割、区域和边界的表示与描述以及目标识别。-Book introduces the basics of MATLAB programming, the main focus on the backbone of the contents of digital image processing t
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Wavelet transforms and other multi-scale analysis functions have been used for compact signal and image representations in denoising, compression and feature detection processing problems for about twenty years. Numerous research works have proven th
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lossy image compression using wavelet...may be lost some data
eng...7ayder
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Choice of Wavelets for Image Compression
In wavelet-based image coding the choice of wavelets is crucial and determines the coding
performance. Current techniques use computationally intensive search procedures to find the optimal basis (type,
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PERCEPTUAL OPTIMIZATION OF WAVELET IMAGE COMPRESSION
NASA’s extensive image compression requirements may be met in part by the use
of wavelet techniques.1 Wavelets form a large class of signal and image transforms,
generally characterized by de
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Scaling, wavelets, image compression, and
encoding
NASA’s extensive image compression requirements may be met in part by the use
of wavelet techniques.1 Wavelets form a large class of signal and image transforms,
generally characterized by de
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Images require substantial storage and transmission resources, thus image compression is advantageous to reduce these requirements. The report covers some background of wavelet analysis, data compression and how wavelets have been and can be used for
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1 Haar Wavelets
1.1 The Haar transform
1.2 Conservation and compaction of energy
1.3 Haar wavelets
1.4 Multiresolution analysis
1.5 Compression of audio signals
1.6 Removing noise from audio signals
1.7 Notes and references
2 Daub ech
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E ective image compression requires a non-expansive discrete wavelet transform (DWT) be
employed consequently, image border extension is a critical issue. Ideally, the image border
extension method should not introduce distortion under compressio
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