Description: 一种新的图像脆弱水印算法李亚琴 ，孙星明 ，杨恒伏(1．苏州市职业大学，江苏苏州215104；2．湖南大学计算机与通信学院，湖南长沙410082)摘要：提出一种基于小波变换和QR分解的图像脆弱水即方法。嵌入水印时，首先对原始图像进行三级小波分解，然后提取第三级低频子带的边缘特征，同时对此边缘特征和第三级垂直高频子带进行QR分解，用边缘特征的一部分分解结果替换垂直高频子带分解结果的相应部位来嵌入水即，最后进行小波逆变换得到嵌入水印的图像。图像认证时，首先对观测图像进行三级小波分解，第三级垂直高频子带与低频子带边缘特征的QR分解结果进行比较，就可以准确认证图像是否经过攻击，并可以精确定位受攻击的部位。实验结果表明此方法的有效性和可行性。-a new image fragile watermarking algorithm Ya-Qin Li, Sun Xingming, Heng Yang Fu (1. Suzhou City Vocational University, Suzhou City in Jiangsu 215104; 2. Hunan University College of Computer and Communication, Changsha, Hunan 410082) Abstract : A wavelet transform based on QR decomposition and the image that the fragile water ways. Embedded watermark, the first of three original image wavelet decomposition, and then extract the third level sub-band edge features, Meanwhile this edge features and third-vertical high-frequency band for QR decomposition, Edge feature with the results of the replacement part of decomposition vertical high-frequency subband results to the corresponding parts of the water that is embedded. Finally inverse wavelet transform embedded watermark images. Image Authen Platform: |
Size: 231599 |
Author:ghostsx |
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Description: 对图像进行2维小波编码 来实现压缩。将小波分析引入图像压缩的范畴也是一个重要的手段，并且有着它自己的特点。它的特点在于压缩比高、压缩速度快，压缩后能保持信号与图像的特征基本不变，且在传递过程中可以抗干扰等等。（有两种方法）-of two-dimensional images wavelet compression coding to achieve. Wavelet Image Compression analysis of the introduction of the context is also an important means, it has its own characteristics. It features is the compression ratio, faster compression, the compressed signal can be maintained with the image of the same basic features, and the transfer process can be interference, etc.. (There are two methods) Platform: |
Size: 3115 |
Author:郭指挥 |
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Description: 一种新的图像脆弱水印算法李亚琴 ，孙星明 ，杨恒伏(1．苏州市职业大学，江苏苏州215104；2．湖南大学计算机与通信学院，湖南长沙410082)摘要：提出一种基于小波变换和QR分解的图像脆弱水即方法。嵌入水印时，首先对原始图像进行三级小波分解，然后提取第三级低频子带的边缘特征，同时对此边缘特征和第三级垂直高频子带进行QR分解，用边缘特征的一部分分解结果替换垂直高频子带分解结果的相应部位来嵌入水即，最后进行小波逆变换得到嵌入水印的图像。图像认证时，首先对观测图像进行三级小波分解，第三级垂直高频子带与低频子带边缘特征的QR分解结果进行比较，就可以准确认证图像是否经过攻击，并可以精确定位受攻击的部位。实验结果表明此方法的有效性和可行性。-a new image fragile watermarking algorithm Ya-Qin Li, Sun Xingming, Heng Yang Fu (1. Suzhou City Vocational University, Suzhou City in Jiangsu 215104; 2. Hunan University College of Computer and Communication, Changsha, Hunan 410082) Abstract : A wavelet transform based on QR decomposition and the image that the fragile water ways. Embedded watermark, the first of three original image wavelet decomposition, and then extract the third level sub-band edge features, Meanwhile this edge features and third-vertical high-frequency band for QR decomposition, Edge feature with the results of the replacement part of decomposition vertical high-frequency subband results to the corresponding parts of the water that is embedded. Finally inverse wavelet transform embedded watermark images. Image Authen Platform: |
Size: 231424 |
Author:ghostsx |
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Description: 图像的小波阈值去噪方法是众多图像去噪
方法中的佼佼者,它利用图像小波分解后,各个子带图像的不同特性,选取不同的阈值,从而达到较好的
去噪效果-Wavelet Image Threshold Denoising Method is one of the many methods of image denoising leader, which uses image wavelet decomposition, each sub-band images of the different features, select a different threshold, so as to achieve better denoising effect Platform: |
Size: 1024 |
Author:weiwei |
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Description: -The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. Mutual Information is the similarity measure used in this case for optimizing the two images. This method requires estimating joint histogram of the two images. The fusion of images is the process of combining two or more images into a single image retaining important features from each. The Discrete Wavelet Transform (DWT) has become an attractive tool for fusing multimodal images. In this work it has been used to segment the features of the input images to produce a region map. Features of each region are calculated and a region based approach is used to fuse the images in the wavelet domain. Platform: |
Size: 67584 |
Author:Harry |
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Description: 一種基于塊樹結構的SPIHT數字圖像壓縮算法: 在分析圖像經過小波變換后所具有的特性的基礎上,提出了一種改進的SPIHT算法.由于低頻系數占據圖像的百分之九十以上的能量,在圖像的重構中十分重要,所以,對這些系數不進行壓縮而直接傳輸 而最高頻系數相對不重要,所以不做處理,只在圖像重構時以指定的數值予以重構,因此不僅提高了圖像的質量,同時提高了圖像的壓縮率.在具體的算法中,提出了塊樹的結構,減少了算法所需的內存,拓寬了算法的應用范圍.-A tree structure based on the SPIHT block of digital image compression algorithm: After the analysis of images after the wavelet transform features, based on a modified SPIHT algorithm. Due to the low frequency coefficient images occupy more than 90 percent of energy in image reconstruction is very important, so these factors do not directly transfer compression The most high-frequency coefficient is relatively unimportant, so no treatment, only when the image reconstruction be designated numerical reconstruction therefore not only improve the image quality, while improving the image compression ratio. algorithms in specific, the proposed block-tree structure, the algorithm to reduce memory requirements and broaden the scope of application of the algorithm. Platform: |
Size: 273408 |
Author:jason.. |
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Description: Linear and non-linear approximation with wavelets
Linear approximation is obtained by keeping M low frequency coefficients and then applying the inverse wavelet transform. Here we take M=n^2/4 by keeping n/2 x n/2 low frequency coefficients.
Linear approximation is obtained by keeping M=n^2/4 best coefficients, that are the M largest amplitude coefficients.
We can now compute the approximation error and display both the coefficients and the resulting images. The non-linear approximation is usually much better for images that contains edges because linear approximation blurs features (it is non-adaptive).
Platform: |
Size: 97280 |
Author:Swati |
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Description: This paper identifies a novel feature space to
address the problem of human face recognition from
still images. This based on the PCA space of the
features extracted by a new multiresolution analysis
tool called Fast Discrete Curvelet Transform. Curvelet
Transform has better directional and edge
representation abilities than widely used wavelet
transform. Inspired by these attractive attributes of
curvelets, we introduce the idea of decomposing
images into its curvelet subbands and applying PCA
(Principal Component Analysis) on the selected
subbands in order to create a representative feature
set. Experiments have been designed for both single
and multiple training images per subject. A
comparative study with wavelet-based and traditional
PCA techniques is also presented. High accuracy rate
achieved by the proposed method for two well-known
databases indicates the potential of this curvelet based
feature extraction method.-This paper identifies a novel feature space to
address the problem of human face recognition from
still images. This is based on the PCA space of the
features extracted by a new multiresolution analysis
tool called Fast Discrete Curvelet Transform. Curvelet
Transform has better directional and edge
representation abilities than widely used wavelet
transform. Inspired by these attractive attributes of
curvelets, we introduce the idea of decomposing
images into its curvelet subbands and applying PCA
(Principal Component Analysis) on the selected
subbands in order to create a representative feature
set. Experiments have been designed for both single
and multiple training images per subject. A
comparative study with wavelet-based and traditional
PCA techniques is also presented. High accuracy rate
achieved by the proposed method for two well-known
databases indicates the potential of this curvelet based
feature extraction method. Platform: |
Size: 432128 |
Author:Swati |
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Description: 基于纹理谱描述子的图像检索
提出一种新的纹理谱描述子应用于基于内容的图像检索中.讨论了小波变换的思想和纹理谱概念的联
系,根据纹理的视觉特性,提出纹理模式等价类的概念,设计出更合理的纹理谱描述子来描述图像的纹理特征.该纹
理模式刻画了领域内像素灰度变化模式,以纹理谱直方图方式表示图像纹理内容.分析了纹理谱的对称不变性和旋
-This paper presents a new texture spectrum descriptor for content-based image retrieval(CBIR).The
relation between wavelet transition and texture spectrum method is discussed.This paper proposes the concept of
texture pattern equivalent according to texture visual nature to educe more rational texture spectrum descriptor.The
proposed texture patterns depict the variational pattern of pixel gray scales in a domain to descript images texture
feature.It represents image content in the form of texture spectrum histogram.The symmetry invariant and rotation
robusticity are discussed.Comparison with Gabor features using general image dataset indicate that the proposed
texture descriptor takes lower extracting time and provides higher image retrieval accuracy.
Platform: |
Size: 759808 |
Author:swx |
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Description: 二维线性鉴别分析(2DLDA)算法能有效解决线性鉴别分析(LDA)算法的“小样本”效应，支持向量机
(SVM)具有结构风险最小化的特点，将两者结合起来用于人脸识别。首先，利用小波变换获取人脸图像的低频分量，忽
略高频分量：然后，用2DLDA算法提取人脸图像低频分量的线性鉴别特征，用“一对多”的SVM 多类分类算法完成人脸
识别。基于ORL人脸数据库和Yale人脸数据库的实验结果验证了2DLDA+SVM算法应用于人脸识别的有效性。-”Small sample size”problem of LDA algorithm can be overcome by two—dimensional LDA f 2DLDA)，and
Support Vector Machine(SVM)has the characteristic of structural risk minimization．In this paper，two methods were
combined and used for face recognition．Firstly，the original images were decomposed into high—frequency and low—frequency
components by Wavelet Transform(WT)．The high—frequency components were ignored，while the low—frequency components
can be obtained．Then．the liner discriminant features were extracted by 2DLDA，and”one VS rest”。strategy of SVMs for
muhiclass classification was chosen to perform face recognition． Experimental results based on ORL f Olivetti Research
Laboratory1 face database and Yale face database show the validity of 2DLDA+SVM algorithm for face recogn ition． Platform: |
Size: 236544 |
Author:费富里 |
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Description: 提出了基于特征融合和模糊核判别分析(FKDA)的面部表情识别方法。首先，从每幅人脸图像中手工定
位34个基准点，作为面部表情图像的几何特征，同时采用Gabor小波变换方法对每幅表情图像进行变换，并提取基
准点处的Gabor小波系数值作为表情图像的Gabor特征；其次，利用典型相关分析技术对几何特征和Gabor特征进
行特征融合，作为表情识别的输人特征；然后，利用模糊核判别分析方法进一步提取表情的鉴别特征；最后，采用最
近邻分类器完成表情的分类识别。通过在JAFFE国际表情数据库和Ekman“面部表情图片”数据库上的实验，证实
了所提方法的有效性。-Proposed based on feature fusion and fuzzy kernel discriminant analysis (FKDA) facial expression recognition. First, face images of each piece of hand-set
Bit 34 basis points, as the geometric features of facial expression images, while using Gabor wavelet transform method to transform the images of each piece of expression, and extraction-based
Quasi-point of the Gabor wavelet coefficients, as Gabor features of facial expression image second, using canonical correlation analysis on the geometric features and Gabor features into
Line feature fusion, as expression recognition of input features then, using fuzzy kernel discriminant analysis method to extract and further identification features of expression Finally, the most
Neighbor classifier to complete expression of the classification. International expression by JAFFE database and Ekman "facial image" database on the experiment, confirmed
The proposed method. Platform: |
Size: 375808 |
Author:MJ |
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Description: 根据遥感图像纹理所呈现的多尺度特性和随机的特性，采用基于小波域
隐马尔可夫树模型对纹理进行分析，并有机地结合遥感图像的要求和特点进行深入研究。
-According to remote sensing image texture features presented and random multi-scale features, based on wavelet domain hidden Markov tree model for texture analysis, and the opportunity to combine the requirements of remote sensing images and features in-depth study. Platform: |
Size: 20836352 |
Author:江涛 |
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Description: 首先对两幅需要进行融合的图像完成小波变换，小波系数位于LL，LH，HL以及HH这4个频带。小波系数的绝对值越大，其对应于更为尖锐的灰度变化（即图像中的突出特征部分），在小波融合中，一个主要的思想便是判断两幅原始图像对应小波系数的绝对值大小。在变换域的每一个小波系数都取绝对值相对大的那一个，这样，便实现了在所有分辨率级别上的小波系数融合，并且新的小波系数完好地保存了更多的频带特征。所有融合后的图像可以通过对新的小波系数进行小波逆变换得到。-First two images need to complete the integration of wavelet transform, wavelet coefficients in the LL, LH, HL, and HH the four frequency bands. The greater the absolute value of wavelet coefficients, which correspond to the more acute the gray scale (ie, the prominent features of the image in part), the wavelet fusion, one of the main thought is to check two pieces of the original image corresponds to the absolute value of wavelet coefficients size. In each wavelet transform domain coefficients that take a relatively large absolute value, so that the resolution will be achieved at all levels of integration of the wavelet coefficients and wavelet coefficients of the new well-preserved features of more frequency bands. All images can be fused by the wavelet coefficients of the new inverse wavelet transform. Platform: |
Size: 881664 |
Author:aluily |
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Description: Gabor wavelet transform applied to feature extraction of ophthalmic images.
We investigate a new approach for measuring ocular
refractive errors (astigmatism, near-sightedness and shortsightedness)
from images of the human eye [1]. This
approach uses Support Vector Machines (SVMs) to
analyse data features extracted from images of the eye
acquired with a technique known as Hartmann-Shack [2]
and output measures for the eye´ s refractive errors. Prior to
analysis and feature extraction an image processing stage
takes place to identify and crop the region of interest
considering domain spatial and geometrical information.
Then a set of relevant image features are extracted using
wavelet and Garbor Transforms. These features are finally
fed into a SVM module for analysis that provides a
diagnosis of refractive errors present in the ocular globe
under investigation. Platform: |
Size: 7168 |
Author:Real |
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Description: A new approach for fingerprint verification, based on wavelets and pseudo Zernike moments (PZMs), is
discussed. PZMs are robust to noisy images, invariant to rotation and have a good image reconstruction
capability [4]. PZMs have been used for global analysis and so they are used to extract global features (the
shape of the fingerprint image). Wavelets are good at local analysis and so they help to extract local
features (minutiae) from a fingerprint. Therefore, this hybrid approach extracts most significant features
from the fingerprint images and achieve better verification rate. Different types of wavelets are used for the
study but the result shows that Symmlet orthonormal wavelet of order 8 gives best verification rate. Platform: |
Size: 386048 |
Author:samira |
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Description: 基于标记的Watershed图像分割算法是一种改进的分水岭算法，它很好地被应用于人脸及其他一些场景图像的分割。把该方法引入高分辨遥感图像的分割，并针对遥感图像的特点，在分割之前采用中值滤波对高分辨率遥感图像进行预处理；同时，在分割过程中采用用小波滤波器替代Butterworth滤波器对梯度图像的低通滤波。不同地物特征Quickbird图像的分割实验表明，对于纹理比较均一的高分辨率遥感图像，该方法避免了过分割现象，且效率较高；但对于纹理比较复杂的图像，该方法具有一定的局限性。-Watershed based image segmentation algorithm tag is an improved watershed algorithm, it well be applied to the face and some other scenes segmentation of images. The introduction of high-resolution remote sensing of the method for segmentation of images and features for remote sensing image, the segmentation using median filtering before the high-resolution remote sensing image is preprocessed also used in the segmentation process Butterworth filter with a wavelet filter replacement the gradient image of low-pass filter. Characteristics of different objects that Quickbird image segmentation, for texture and uniform high-resolution remote sensing images, the method avoids over-segmentation phenomenon, and efficient but more complex texture images, this method has some limitations .
Platform: |
Size: 973824 |
Author:xiliao |
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Description: 包括图像增强小波变换加载相关图片等功能 是图像处理的方便比较常用的一些基本变换-Including the wavelet transform image enhancement features such as load-related images is commonly used image processing to facilitate some of the basic transformation Platform: |
Size: 32185344 |
Author:张华 |
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Description: Image Fusion is the process of combining information of two or more images into a single image which can retain all important features of the all original images. Input to fusion is a set of images taken from different modalities of the same scene. Output is an image of better quality which quality depends on a particular application. The objective of fusion is to generate a resultant image which describes a scene better or even higher than any single image with respect to some relevant properties providing a highly informative image. These fusion techniques are especially beneficial in diagnosing and treating cancer in field of medicine. This paper focuses on the development of a different image fusion method using Dual Tree Complex Wavelet Transform. Experimental results show that the proposed algorithm has a better visual quality than the base methods. Also the result if the fused image has been evaluated using a set of quality metrics. -Image Fusion is the process of combining information of two or more images into a single image which can retain all important features of the all original images. Input to fusion is a set of images taken from different modalities of the same scene. Output is an image of better quality which quality depends on a particular application. The objective of fusion is to generate a resultant image which describes a scene better or even higher than any single image with respect to some relevant properties providing a highly informative image. These fusion techniques are especially beneficial in diagnosing and treating cancer in field of medicine. This paper focuses on the development of a different image fusion method using Dual Tree Complex Wavelet Transform. Experimental results show that the proposed algorithm has a better visual quality than the base methods. Also the result if the fused image has been evaluated using a set of quality metrics. Platform: |
Size: 16384 |
Author:sruthy78 |
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Description: some fast feature extraction algorithms are addressed for joint retrieval of images
compressed in JPEG and JPEG2000 formats. In order to avoid full decoding, three fast algorithms that
convert block-based discrete cosine transform (BDCT) into wavelet transform are developed, so that
wavelet-based features can be extracted from JPEG images as in JPEG2000 images. Platform: |
Size: 523264 |
Author:1212login |
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Search - wavelet images features