Vector quantization in DCT domain using fuzzy possibilistic c-means based on penalized and compensated constraints

In this paper, fuzzy possibilistic c-means (FPCM) approach based on penalized and compensated constraints are proposed to vector quantization (VQ) in discrete cosine transform (DCT) for image compression. These approaches are named penalized fuzzy possibilistic c-means (PFPCM) and compensated fuzzy possibilistic c-means (CFPCM). The main purpose is to modify the FPCM strategy with penalized or compensated constraints so that the cluster centroids can be updated with penalized or compensated terms iteratively in order to find near-global solution in optimal problem. The information transformed by DCT was separated into DC and AC coefficients. Then, the AC coefficients are trained by using the proposed methods to generate better codebook based on VQ. The compression performances using the proposed approaches are compared with FPCM and conventional VQ method. From the experimental results, the promising performances can be obtained using the proposed approaches.     

基于改进的模糊C均值算法的MR图像分割

在利用模糊C均值算法(FCM)对磁共振图像进行分割的基础上,提出了一种改进的模糊分割技术。实验结果表明,该方法与FCM算法相比,不仅能够更为准确地分割出人脑组织中的各个部分,同时运行速度也有明显提高。     

模糊C均值聚类与硬聚类的性能比较及改进

本文以灰度值的图像分割为基础,对模糊C均值聚类算法(Fuzzy C-means,FCM)[1]和硬聚类进行了详尽的讨论,在此基础上对两者进行了比较,包括两者的迭代速度比较和两者的分割效果比较,聚类中心的初始化对迭代速度和分割效果的影响,并以此为基础对FCM聚类算法进行了改进。实验表明,改进的FCM聚类算法在迭代速度和分割效果方面都明显优于原始的FCM聚类算法。     

一种基于非均值量化系数特征不变的盲数字水印方案

针对商品包装图像在水印检测过程中图像会发生变形的问题展开研究,提出一种基于非均值量化系数特征不变的盲数字水印方案。该方案利用第二代数字水印的概念,采用了量化水印技术,通过图像内容的重要系数特征进行水印的提取,解决了商品包装图像在图像发生弯曲变形的情况下水印的检测问题。实验结果表明,该方法在保证水印的不可见性的同时,具有较大水印容量,在商品有较大角度偏转和位移的情况仍能正确提取,对于常见的图像旋转、平移、剪切和扭曲等攻击具有鲁棒性。     

利用多进制小波变换和模糊c-均值聚类进行纹理分割

提出了一种基于多进制小波变换的多纹理特征提取方法,通过对小波系数的标准差作为纹理测度以生成特征向量,利用模糊c-均值聚类算法进行纹理分割,获得了较好的实验结果。     

模糊C均值聚类算法在多元图像分割中的应用

改进的模糊C均值聚类算法在对多元图像进行分割的过程中,通过给图像中各个类的对象分配不同的权值来提高模糊C均值聚类算法对不同大小类的敏感性。实验证明,经过改进的模糊C均值聚类算法克服了原始算法对多元图像中类大小敏感性差的问题。     

离散余弦变换在心电信号压缩中的应用研究

目前心电（ECG）信号压缩是生物医学信号压缩的一个热门研究领域.临床诊断过程中,心电信号的存储与传输是一个有待解决的问题,由于采集到的原始信号数据量巨大,为了便于对大量的心电数据进行存储、分析和传输,对于这些数据的压缩处理是十分必要的.通过对心电数据压缩方法的概述与讨论,在研究国内外有关心电信号数据压缩算法及其研究状况的基础上,采用了离散余弦变换（DCT）算法对心电信号进行压缩,取得了较高的压缩比和保真度,具有一定的应用价值.     

MATLAB在数字水印中的应用

探讨MATLAB在数字水印中的应用，利用MATLAB语言编程实现了一类数字水印算法的嵌入、攻击及提取过程,并给出了程序运行的结果。     

一种基于DWT的自适应大容量音频水印算法

提出了一个自适应的音频水印嵌入算法。对音频载体和水印图像分别进行了离散小波变换和离散余弦变换,根据人类听觉系统的时域掩蔽效应选择嵌入点,在小波系数中的对应位置嵌入水印信号。嵌入水印后的音频信号觉察不出明显的变化,并且嵌入后的水印具有较高的鲁棒性。     

Color image segmentation using histogram thresholding - Fuzzy C-means hybrid approach

This paper presents a novel histogram thresholding - fuzzy C-means hybrid (HTFCM) approach that could find different application in pattern recognition as well as in computer vision, particularly in color image segmentation. The proposed approach applies the histogram thresholding technique to obtain all possible uniform regions in the color image. Then, the Fuzzy C-means (FCM) algorithm is utilized to improve the compactness of the clusters forming these uniform regions. Experimental results have demonstrated that the low complexity of the proposed HTFCM approach could obtain better cluster quality and segmentation results than other segmentation approaches that employing ant colony algorithm.     

基于训练样本自动选取的SVM彩色图像分割方法

图像分割是模式识别、图像理解、计算机视觉等领域的重要研究内容。基于支持向量机((Support Vcctor Ma-chine, SVM)的方法现已广泛应用于图像分割,但其在训练样本的选取上大多是人工选择,这降低了图像分割的自适应性,且影响了SVM的分类性能。提出一种基于训练样本自动选取的SVM彩色图像分割方法,算法首先使用模糊C均值(Fuzzy C-Mcans, FCM)聚类算法自动获取训练样本,然后分别提取图像颜色特征和纹理特征,将其作为SVM模型训练样本的特征属性进行训练,最后用训练好的分类器对图像进行分割。实验结果表明,提出的方法可取得很好的分割结果。     

基于全局优化搜索算法的图像分割研究

基于聚类的图像分割算法中,由于模糊C-均值算法需要初始化,并且目标函数存在许多局部极小点,如果初始化落在目标函数的局部极小点附近,就会造成算法收敛到局部极小.为了解决此问题,采用全局优化搜索算法,提出了将全局优化搜索技术引入进来对模糊C-均值算法加以改进,分析了在不同初始条件下,对许多样本的聚类分析时,全局优化搜索算法比传统的模糊C-均值聚类算法更加有效,通过仿真实验验证并对算法性能进行理论分析.     

基于JPEG的图像检索综述

基于内容的检索是近年来的研究热点之一,现在已有许多基于象素域的图像检索技术,目前数据压缩也已成为多媒体应用的标准模式,静态图像压缩主要采用JPEG技术,研究基于传统JPEG和JPEG2000的图像检索方法成为必然。本文综述近年来出现的基于JPEG核心算法离散余弦变换和JPEG2000核心算法离散小波变换的图像检索技术。     

基于聚类余弦变换的图像增强算法研究

研究提高图像清晰度问题,由于一些拍照设备由于抖动造成图像不清,或者图像噪声的干扰造成图像不清晰等问题。针对传统的图像增强算法容易导致分块效应等问题,为了提高图像增强后的图像质量,提出了一种多尺度离散余弦变换和均值聚类相结合的改进的图像增强算法。首先将图像中的基本小块合并为较大的矩阵,从而获得更大范围的图像增强系数,避免了图像小块之间的不相关性。然后根据不同波段的不同特性,使用自适应的增强系数,使得图像不同区域内的增强效果更依赖于自身的特性,最后采用均值聚类对图像进行平滑处理,提高整幅图像的亮度和对比度,获得最终的增强图像。仿真结果表明提出的改进算法有效提高了图像的清晰度,图像更为平滑,同时提高了图像增强效果。     

Implementation of an online DCT based time-varying delay estimator using systolic arrays

Time-delay estimation process is developed in the transform domain where discrete cosine transform (DCT) coefficients of time-varying delay signals are estimated. The DCT is very efficient in compacting the signal energy in a small number of coefficients. Hence, estimation of time-varying delay is obtained through calculation of small number of DCT coefficients. Online maximum likelihood estimator of time-varying delay is developed in which coefficients of the transformed delay signal are obtained by maximizing the likelihood function in terms of these DCT coefficients. A systolic array architecture is designed to implement the developed algorithm.     

基于离散余弦变换的数字地图水印算法

设计了一个基于DCT的数字地图水印算法.算法首先提取地图数据的特征点,组成特征图像.然后对特征图像作离散余弦变换,把水印信息嵌入在中低频系数上.实验表明,所提算法是高效、安全、鲁棒的.     

基于自适应滤波的快速广义模糊C均值聚类图像分割

快速广义模糊C均值聚类(FGFCM)在对高噪声图像进行聚类分割时,噪声容易导致聚类中心发生偏移,影响图像分割结果.为此,文中提出基于自适应滤波的快速广义模糊C均值聚类算法,用于图像分割.首先根据非局部像素的噪声概率自适应确定参数平衡因子,更准确地反映图像包含的空间结构信息.然后利用该平衡因子有效结合FGFCM中的线性加权和滤波图像与原始图像的中值滤波图像,由于得到的自适应滤波图像根据图像中像素为噪声的概率自适应确定滤波程度,因此可以提高算法对噪声的动态抑制能力.实验表明,相比模糊C均值聚类和FGFCM,文中算法在对噪声含量较高的图像进行聚类分割时,可以得到更准确的结果.     

Adaptive fuzzy wavelet algorithm for text-independent speaker recognition

In this letter, a two-stage approach based on adaptive fuzzy C-means and wavelet transform clustering is proposed for efficient feature extraction of speaker recognition. Besides, the investigation includes the development of objective function for minimizing under unsupervised mode of training. Experimental results show that the speaker recognition rate is 95%.     

基于混沌置乱和混合变换域的扩频水印方案

本文基于混沌置乱和DWT和DCT混合变换域提出了一种扩频数字水印方案,首先对原始水印信息进行混沌置乱预处理,然后应用扩频技术,选取m-序列作为扩频码,对置乱预处理后的水印信息进行扩频,产生扩频水印信息,在充分考虑人眼视觉特性的基础上确定扩频水印在DWT和DCT混合变换域的嵌入位置和强度,扩频增益因子的选取大小取决于所选用的DWT和DCT混合变换域系数的个数以及水印大小。实验结果表明,应用文中提出的基于混沌置乱和混合变换域的扩频水印方案,不但水印的安全性有了很大程度提高,而且对剪切、旋转等各种几何失真攻击和常见的信号处理如噪音、JPEG压缩和滤波攻击具有很强的鲁棒性,即使嵌有水印的图像遭受攻击后受损较严重,水印信息还是能够完好地提取出来。     

An adaptive unsupervised approach toward pixel clustering and color image segmentation

This paper proposes an adaptive unsupervised scheme that could find diverse applications in pattern recognition as well as in computer vision, particularly in color image segmentation. The algorithm, named Ant Colony-Fuzzy C-means Hybrid Algorithm (AFHA), adaptively clusters image pixels viewed as three dimensional data pieces in the RGB color space. The Ant System (AS) algorithm is applied for intelligent initialization of cluster centroids, which endows clustering with adaptivity. Considering algorithmic efficiency, an ant subsampling step is performed to reduce computational complexity while keeping the clustering performance close to original one. Experimental results have demonstrated AFHA clustering's advantage of smaller distortion and more balanced cluster centroid distribution over FCM with random and uniform initialization. Quantitative comparisons with the X-means algorithm also show that AFHA makes a better pre-segmentation scheme over X-means. We further extend its application to natural image segmentation, taking into account the spatial information and conducting merging steps in the image space. Extensive tests were taken to examine the performance of the proposed scheme. Results indicate that compared with classical segmentation algorithms such as mean shift and normalized cut, our method could generate reasonably good or better image partitioning, which illustrates the method's practical value.