3971002xiaobo

说明：  近年来，随着互联网的高速发展，网上的多媒体信息也急剧增加，这些多媒体信息以图像为主。如何从浩瀚的图像数据库中快速、准确地找出所需要的图像，己成为一个备受关注的研究课题。有效地组织、管理和检索大规模的图像数据成为迫切需要解决的问题。于是基于内容的图像检索(Content-Based Image Retrieval: CBIR)作为一个崭新的研究领域出现了。 本课题拟研究、分析彩色图像红、绿、蓝三基色直方图的生成、特征提取和相似度等问题，应用图像的颜色信息—三基色直方图对图像进行检索。针对基于颜色的图像检索，本文采用应用广泛的RGB颜色空间来表示图像的颜色特征，对颜色分量进行等间隔量化并形成特征矢量并对特征矢量进行归一化处理，采用图像均匀分块的方法引入图像中色彩所处的位置信息，用距离度量函数进行图像的相似性匹配。在此基础上实现了基于三基色直方图算法的检索系统。 本文的研究和实践对于促进基于内容的图像数据库检索技术的应用具有一定的参考价值和实践意义。 (With the rapid development of Internet, the multimedia information is booming. All this information is mostly images. Effective recognizing, management and searching all these images have been an emergent problem. This has led the rise of a new research and development field: Content-Based Image Retrieval (CBIR). The topics to research, analysis color images red, green and blue color histogram generation, feature extraction and the similarity of the issues, application of the color image- trichromatic histogram of the image retrieval. Based on the color against the static image retrieval, this paper application of a wide range of RGB color space to indicate the color image features, the color components, such as spacing and quantitative characteristics of a feature vector and a normalization of vector processing, using uniform image block the introduction of the method in which the color image Location information, and distance measuring function similar to the image of the match. On)

用matlab实现的短时傅里叶变换和小波变换。有文档(Using matlab to achieve short-time Fourier transform and wavelet transform. A document)

线调频小波路径追踪算法的程序，对研究瞬时频率估计有很大的参考价值。(Chirplet path tracing algorithm of the program, the study of instantaneous frequency is estimated that there is a great reference value.)

说明：  真正的3 d双树离散小波变换(DWT)的一个数据集x是使用四个严格采样实现可分3 d DWTs在平行。然后subbands四DWTs结合适当。 (The real the 3 d Doubletree discrete wavelet transform (DWT) data set x four to strict sampling separable 3 d the DWTs In parallel. The then the subbands four DWTs combined appropriately.)

对地震数据进行gabor反褶积处理，有实例验证方法，简单易懂(The seismic data are processed by Gabor deconvolution.There are examples of methods to verify, easy to understand)

说明：  小波变化代码，是比较好的测试向量，包括位平面编码和MQ(Wavelet transform code, is a better test vectors, including the bit plane coding and MQ)

基于小波变换的数字盲水印及对嵌入水印后图像的攻击检测(Attack detection based on wavelet transform digital blind watermark and the watermarked image)

用于进行小波变换，对原始的光谱图像数据进行预处理(Used wavelet transform, the original spectral image data preprocessing)

Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously with a smooth reconstructed image. Both contourlets as well as complex-valued dual-tree wavelets are considered for their highly directional representation, while bivariate shrinkage is adapted to their multiscale decomposition structure to provide the requisite sparsity constraint. Smoothing is achieved via a Wiener filter incorporated into iterative projected Landweber compressed-sensing recovery, yielding fast reconstruction. The proposed approach yields images with quality that matches or exceeds that produced by a popular, yet computationally expensive, technique which minimizes total variation. Additionally, reconstruction quality is substantially superior to that from several prominent pursuits-based algorithms that do not include any smoothing

利用小波变换，通过设置阈值对图像进行去噪。 首先对图像用小波进行2层分解，然后通过设置硬阈值和软阈值的方法，对图像高频部分去噪。(The wavelet transform is used to denoise the image by setting threshold. Firstly, the image is decomposed into 2 layers by wavelet, and then the high frequency part of the image is denoised by setting the hard threshold and the soft threshold.)