基于纹理和高斯密度特征的图像检索算法

直接从DCT域中提取图像的特征是提高图像的检索效率的方法.直接从压缩域中提取图像的高斯密度,即计算图像在8个方向上的分段累加值,形成一个8*4的二维向量,再结合图像的纹理特征来进行图像检索.为了验证算法的可行性,建立了10000幅图像的图像库.实验结果表明,该方法能够准确地检索出目标图像,有效地提高了图像检索的精度和速度.     

基于局部DCT系数的图像压缩感知编码与重构

引入了压缩感知(Compressed sensing, CS)理论, 给出了在获取局部二维 离散余弦变换(Discrete cosine transform, DCT)系数的基础上高质量地编码与重构图像的新方法. 研究了在无量化和有量化情况下, 基于局部DCT系数的图像CS最小全变差重构算法. 在对DCT系数进行量化的过程中得到含噪的局部DCT系数, 在此基础上设计了能完成CS重构的图像编解码一般流程, 并构建了实际应用系统. 实验结果表明, 对于稀疏性较强的图像, 在图像编解码系统中结合CS理论与方法能得到高质量的重构图像, 与传统的直接反离散余弦变换(Inverse DCT, IDCT)方法相比, 峰值信噪比(Peak signal to noise ratio, PSNR)最大能提高5dB以上, 对于一般图像, PSNR也有较大提高.     

Image retrieval based on index compressed vector quantization

Increased amount of visual data in several applications necessitates content-based image retrieval. Since most of visual data is stored in compressed form, it is crucial to develop indexing techniques for searching images based on their content in compressed form. Therefore, it is desirable to explore image compression techniques with capability of describing image content in compressed form. Vector Quantization (VQ) is a compression scheme that exploits intra-block correlation and image correlation reflects image content, hence VQ is a suitable compression technique for compressed domain image retrieval.This paper introduces a novel indexing scheme for compressed domain image databases based on indices generated from IC-VQ. The proposed scheme extracts image features based on relationship between indices of IC-VQ compressed images. This relationship detects contiguous regions of compressed image based on inter- and intra-block correlation. Experimental results show effectiveness superiority of the new scheme compared to VQ and color-based schemes.     

半空间混合图像置乱方法

考虑到变换域置乱的鲁棒性和混沌序列对初值敏感、遍历性及随机性等特点,提出一种基于DCT变换域的半空间图像置乱方法,先对图像的第一个变量进行一维DCT变换。在此基础上对DCT系数用混沌序列进行调制,将调制结果进行DCT反变换;进而对图像的第二变量进行一维DCT变换,采用与第一变量相同的方法得到最终的置乱结果。算法简单可行,置乱效果好。实验证明该方法具有一定的抗攻击能力。     

基于统计特征的DCT压缩域纹理图像检索方法

提出了一种基于离散余弦变换（Discrete Cosine Transfrom,DCT）的纹理图像的检索方法.该方法在DCT压缩域,通过直接对DCT系数计算,获得图像纹理的统计特征,并作为检索的依据.理论分析和实验结果都表明,该方法具有很好的检索准确率和效率,并且对于旋转具有不变性.     

基于JPEG二进制压缩流的隐写分析

提出一种基于JPEG二进制压缩数据流的隐写分析方法。该方法不同于在基于离散余弦变换频率域以及图像空间域上的隐写分析方法,利用嵌入信息引起二进制压缩流熵的变化,应用多重嵌入方法得到一组特征向量,以此训练一类支持向量机。针对JSteg和Outguess嵌入方法的检测实验达到了较理想的效果。     

JPEG compressed image retrieval via statistical features

To improve efficiency of compressed image retrieval, we propose a novel statistical feature extraction algorithm in this paper to characterize the image content directly in its compressed domain. The statistical feature extracted is mainly through computing a set of moments directly from DCT coefficients without involving full decompression or inverse DCT. Following the algorithm design, a content-based image retrieval system is implemented especially targeting retrieving joint picture expert group compressed images. Theoretical analysis and experimental results support that the system is robust to translation, rotation and scale transform with minor disturbance, and the system achieves good performances in terms of retrieval efficiency and effectiveness.     

DCT域中任意比例的图像上下采样算法

在许多实际应用中, 为了满足传输信道和终端显示设备的要求, 需要通过上采样和下采样来改变图像的尺寸. 压缩域中的图像上下采样可以在空域中进行, 然而, 直接在压缩域中实现将更为快速. 本文根据空域中块与子块的相互关系以及酉变换对矩阵乘法的分配率, 提出了 DCT 域内任意比例图像上下采样算法. 与现存的算法相比, 本算法具有较高的信噪比, 较低的运算复杂度, 并适用于帧内与帧间编码的不同情况, 可应用于不同视频编码转码的实时处理.     

基于Retinex理论的压缩域图像增强方法研究

针对现有压缩域图像增强算法在提高图像对比度时,存在不能很好地增强图像细节及保持色彩信息的局限性,提出一种新的基于Retinex理论的DCT压缩域图像增强算法.该算法以Retinex理论为基础,将DCT系数分为入射分量(DC系数)和反射分量(AC系数),通过对DC系数进行动态范围调整,对AC系数进行细节增强调整,并使用阈...     

Image database indexing using JPEG coefficients

Image database indexing is used for efficient retrieval of images in response to a query expressed as an example image. The query image is processed to extract information that is matched against the index to provide pointers to similar images. We present a technique that facilitates content similarity-based retrieval of jpeg-compressed images without first having to uncompress them. The technique is based on an index developed from a subset of jpeg coefficients and a similarity measure to determine the difference between the query image and the images in the database. This method offers substantial efficiency as images are processed in compressed format, information that was derived during the original compression of the images is reused, and extensive early pruning is possible. Initial experiments with the index have provided encouraging results. The system outputs a set of ranked images in the database with respect to the query using the similarity measure, and can be limited to output a specified number of matched images by changing the threshold match.     

Combined frequency and spatial domain-based patch propagation for image completion

Film and photography archives now have an accelerated rate of degradation. Because the preservation of cultural heritage plays an important role in our society, photograph and film restoration has recently drawn a substantial amount of attention. In this paper, an approach that involves exemplar-based inpainting, aimed at determining patch priority and patch matching, is proposed. Different image regions have different levels of importance for vision perception; hence, a priority score must be assigned. Patch priority is calculated by the energy of its distributed cosine transform coefficients (DCT term) and the edge term. The edge term prioritizes the edge patches and the energy of the DCT coefficients of the patch is used as a discriminator for patches with similar edge terms. Patch inpainting is performed by assessing the similarity between the patches in such a manner that the similarity measure is consistent with human visual judgment. Therefore, a structure-based similarity measure is developed. Further, the interpolated missing pixels at the patch are also considered for applying the structure-based patch matching criteria in finding the candidate patch. Experimental results on damaged digitized photographs and natural images are presented, which demonstrate the effectiveness of the image completion framework for tasks such as scratch/text, object removal and image inpainting.     

Fuzzy C-Means clustering through SSIM and patch for image segmentation

In this study, we propose a new robust Fuzzy C-Means (FCM) algorithm for image segmentation called the patch-based fuzzy local similarity c-means (PFLSCM). First of all, the weighted sum distance of image patch is employed to determine the distance of the image pixel and the cluster center, where the comprehensive image features are considered instead of a simple level of brightness (gray value). Second, the structural similarity (SSIM) index takes into account similar degrees of luminance, contrast, and structure of image. The DSSIM (distance for structural similarity) metric is developed on a basis of SSIM in order to characterize the distance between two pixels in the whole image. Next a new similarity measure is proposed. Furthermore, a new fuzzy coefficient is proposed via the new similarity measure together with the weighted sum distance of image patch, and then the PFLSCM algorithm is put forward based on the idea of image patch and this coefficient. Through a collection of experimental studies using synthetic and publicly available images, we demonstrate that the proposed PFLSCM algorithm achieves improved segmentation performance in comparison with the results produced by some related FCM-based algorithms.     

基于块边缘模式的图像内容描述符

本文提出一种有效的基于从图像压缩域提取的块边缘模式的内容描述符,它特别适用于JPEG压缩图像或MPEG压缩视频.该图像内容描述符由三种块边缘模式的游程编码直方图构成.大量的实验结果证明,与现行的类似算法相比,本文提出的算法在进行图像检索时,具有更高的平均查准率和查全率.     

基于数据隐藏的图像检索系统

本文提出一种新的图像检索系统,采用数据隐藏算法把图像的标注信息和特征信息嵌入压缩域图像中,用于快速检索。由于DCT在图像压缩中得到了广泛的应用,本文分析了基于DCT的JPEG图像格式编码流程,实现了一种基于JPEG压缩的数据隐藏算法。实验结果表明,该算法未引起图像质量明显下降,可嵌入较多数据。     

压缩域中基于自动标记的图像分割

针对传统像素域中图像分割算法计算复杂的缺陷,提出了一种压缩域中快速图像分割算法。对图像分块,提取离散余弦变换（DCT）系数结合颜色矩作为块特征,利用支持向量机（SVM）实现对压缩域中图像块的自动标记,采用提出的阈值最小生成树（TMST）算法对已标记块进行区域生长,应用形态学相关算法对分割出的图像进行修补。通过Corel图像数据库对提出的方法进行验证,结果表明该方法能够更加快速有效地进行图像分割。     

DCT域中的快速分形编码

分形图像压缩应用了图像的自相似性，目前许多对分形编码特性的研究都是在图像域中进行的。该文却试图探索在频率域中分形编码的特性。首先，综述了图像域中分形编码的特性，然后导出在离散余弦变换（简称DCT）域中仿射变换的伸缩因子和偏移量的对应公式。应用DCT的能量压缩特性，在度量图像子块和母块之间相似性中通过使用少量的低频DCT系数提出一种快速分形编码算法。接着进一步提出一种可能的快速混合分形编码的算法，该算法将快速搜索方法、统计规范化、频域比较结合起来。     

基于稀疏梯度场的非局部图像去噪算法

非局部平均(Non-local means, NLM)算法充分利用图像的自相似性与结构信息的冗余性, 取得了很好的去噪效果.然而, 在强噪声的干扰下, NLM算法中的权函数不能准确度量图像块之间的相似性. 因此, 很多文献利用图像的梯度信息对权函数做了改进.但是, 传统的梯度算子对噪声十分敏感, 不能有效地提高相似性度量的准确性. 本文将图像的稀疏梯度场(Sparse gradients field, SGF)引入权函数的定义中, 提出一种基于稀疏梯度场的非局部图像去噪算法. 首先, 区别于传统基于局部的梯度算子, 提出了基于全局的稀疏梯度场模型, 进一步给出一个自适应的稀疏梯度场模型(Adaptive sparse gradients field, ASGF), 并利用向前--向后分裂算法求解.然后, 利用图像的稀疏梯度场对NLM算法的权函数进行改进, 得到本文提出的算法.实验结果表明, 无论是客观评价还是视觉效果, 本文所提算法的性能优于NLM 算法和其他利用梯度信息改进的NLM算法.     

DCT压缩域中图像颜色布局描述符的提取

在国际标准MPEG-7所建议的一种颜色布局描述符基础上,针对JPEG压缩图像,阐述了在DCT压缩域中,从Y、Cb、Cr颜色分量图像的各个8×8子块的直流分量中直接提取颜色布局描述符,以方便于在压缩域中根据颜色的空间分布特征进行快速的图像索引和图像检索。