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检索条件"任意字段=Conference on Wavelet Applications in Signal and Image Processing VII"

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image super-resolution reconstruction based on self-similarity and neural networks

Image super-resolution reconstruction based on self-similari...

引用

2012 11th International conference on Information Science, signal processing and their applications, ISSPA 2012

作者： Xu, Yan Li, Xue M. Gao, Tian Suen, Ching Y. Beijing Key Laboratory of Network System and Network Culture University of Posts and Telecommunications Beijing 100876 China Centre for Pattern Recognition and Machine Intelligence Concordia University Montreal QC H3G 1M8 Canada School of Computer Shandong Jianzhu University Jinan 250101 China

ISBN: (纸本)9781467303828

A novel super-resolution approach is presented. An image pyramid has been built based on the framework of wavelet transform, and the detailed coefficients are explored for training the neural networks. The initial high resolution image is estimated by the trained networks and the inverse wavelet transform, and then is constrained with prior knowledge of the error function by iteration. For a factor of 2n, repeat this process and update the networks. The experimental results show that our method reconstructs the more reliable image without obvious visual artifacts. © 2012 IEEE.

关键词： wavelet transforms

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image manipulation detection using contourlet transform

Image manipulation detection using contourlet transform

引用

2012 20th signal processing and Communications applications conference, SIU 2012

作者： Özparlak, Levent Avcibaş, Ismail Elektrik Ve Elektronik Mühendisliǧi Bölümü Başkent Üniversitesi Turkey Elektrik Ve Elektronik Mühendisliǧi Bölümü Turgut Özal Üniversitesi Turkey

In this paper, we use contourlet transform for digital image manipulation detection. We extract contourlet and wavelet features and test these obtained features on a controlled image data set. Results show that contou... 详细信息

ISBN: (纸本)9781467300568

关键词： Statistical tests

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New image Compression Algorithm based on Improved Reversible Biorthogonal Integer wavelet Transform

New Image Compression Algorithm based on Improved Reversible...

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conference on applications of Digital image processing XXXV

作者： Zhang, Libao Yu, Xianchuan Beijing Normal Univ Coll Informat Sci & Technol Beijing 100875 Peoples R China

ISBN: (纸本)9780819492166

The low computational complexity and high coding efficiency are the most significant requirements for image compression and transmission. Reversible biorthogonal integer wavelet transform (RB-IWT) supports the low computational complexity by lifting scheme (LS) and allows both lossy and lossless decoding using a single bitstream. However, RB-IWT degrades the performances and peak signal noise ratio (PSNR) of the image coding for image compression. In this paper, a new IWT-based compression scheme based on optimal RB-IWT and improved SPECK is presented. In this new algorithm, the scaling parameter of each subband is chosen for optimizing the transform coefficient. During coding, all image coefficients are encoding using simple, efficient quadtree partitioning method. This scheme is similar to the SPECK, but the new method uses a single quadtree partitioning instead of set partitioning and octave band partitioning of original SPECK, which reduces the coding complexity. Experiment results show that the new algorithm not only obtains low computational complexity, but also provides the peak signal-noise ratio (PSNR) performance of lossy coding to be comparable to the SPIHT algorithm using RB-IWT filters, and better than the SPECK algorithm. Additionally, the new algorithm supports both efficiently lossy and lossless compression using a single bitstream. This presented algorithm is valuable for future remote sensing image compression.

关键词： image compression integer wavelet transform lifting scheme SPIHT optimal coefficient scaling

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Single image superresolution using sparsity and dictionary learning in wavelet domain

Single image superresolution using sparsity and dictionary l...

引用

2012 20th signal processing and Communications applications conference, SIU 2012

作者： Nazzal, Mahmoud Özkaramanli, Hüseyin Elektrik Ve Elektronik Mühendisliǧi Bölümü Doǧu Akdeniz Üniversitesi Turkey

ISBN: (纸本)9781467300568

Recently sparse representation is proven to be very successful for image processing applications. This paper proposes a superresolution approach that utilizes the decorrelating and sparsifying property of discrete wavelet transform, with the signal-fitting capability of sparse representation over learned dictionaries. Two dictionaries are learned (using K-SVD algorithm) for each wavelet subband: one for the low resolution one for the high resolution images. In the training set, noisy variants of the high a resolution image obtained by interpolating its low resolution counter-part, are intentionally included. A patch based approach is employed and different patch sizes are studied. The sparse representation coefficients for the respective low and high resolution images are assumed to be the same. Experiments are conducted using the Kodak24-image set. The proposed algorithm is proven to be competitive with the leading super-resolution techniques both visually and quantitatively. With a patch size of 11x11 the proposed method is 0.89 dB better than the method proposed by Elad ***. and 2. 19 dB better than bicubic interpolation. © 2012 IEEE.

关键词： Discrete wavelet transforms

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image INPAINTING IN MICROMETEOROLOGICAL ANALYSIS

IMAGE INPAINTING IN MICROMETEOROLOGICAL ANALYSIS

引用

19th IEEE International conference on image processing (ICIP)

作者： Ramirez, Carlos Arguez, Miguel Jaimes, Aline Tweedie, Craig E. Univ Texas El Paso Computat Sci Program El Paso TX 79968 USA Univ Texas El Paso Environm Sci & Engn Program El Paso TX 79968 USA

ISBN: (纸本)9781467325332;9781467325349

Digital image inpainting is the process by which corrupted or defective areas in an image are systematically corrected. New digital image inpainting techniques have been developed in recent years, leading to numerous successful applications, particularly in the are of image restoration. We propose a new image inpainting algorithm base don wavelet sparse representation, and extend its applicability as a new approach for gap-filling in micrometeorological data. Our approach consists of treating the incomplete data set as a structured image that has a sparse representation in the wavelet domain. Therefore, an l(1) minimization problem is formulated in order to characterize the sparsest solution associated with the complete data set. A numerical experimentation on a real micrometeorological data set is conducted, demonstrating the effectiveness of the proposed approach.

关键词： image interpolation Inpainting Gap-filling in Micrometeorology Sparse Representation

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A comparative analysis of image fusion methods

A comparative analysis of image fusion methods

引用

2012 20th signal processing and Communications applications conference, SIU 2012

作者： Kösesoy, Irfan Tepecik, Abdulkadir Çetin, Müfit Mesut, Altan Bilgisayar Mühendisliǧi Bölümü Yalova Üniversitesi Turkey Bilgisayar Mühendisliǧi Bölümü Trakya Üniversitesi Turkey

ISBN: (纸本)9781467300568

In literature, several methods are available to combine both low spatial multispectral and low spectral panchromatic resolution images to obtain a high resolution multispectral image. One of the most common problems encountered in these methods is spectral distortions introduced during the merging process. At the same time, the spectral quality of the image is the most important factor affecting the accuracy of the results in many applications such as object recognition, object extraction, image analysis. In this study, the most commonly used methods including GIHS, GIHSF, PCA and wavelet are analyzed using image quality metrics such as SSIM, ERGAS and SAM. At the same time, wavelet is the best method for obtaining the fused image having the least spectral distortions according to obtained results. At the same time, image quality of GIHS, GIHSF and PCA methods are close to each other, but spatial qualities of the fused image using the wavelet method are less than others. © 2012 IEEE.

关键词： Object recognition

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Development of Discrete wavelet Transform (DWT) toolbox for signal processing applications

Development of Discrete Wavelet Transform (DWT) toolbox for ...

引用

2012 International conference on Biomedical Engineering, ICoBE 2012

作者： Wali, Mousa K. Murugappan, M. Ahmad, R. Badlishah Zheng, Bong Siao School of Computer Engineering University Malaysia Perlis Kuala Malaysia

ISBN: (纸本)9781457719899

Discrete wavelet Transform (DWT) plays a significant role in several image and signal processing applications. Most of the researchers are using different wavelet toolboxes for their application and research investigation. In this work, we presented a development of DWT toolbox using Visual Basic 6.5. This starting version of this software package is developed to offer more user friendliness and allow the user to choose different types of wavelet functions from three different wavelet families (Daubechies, Symlet, and Coiflet), and number of decomposition level. This software is also have an ability to plot the frequency spectrum of user specific decomposition level using Fast Fourier Transform (FFT) and to provide a option for saving the DWT output in *** *** format for any further investigation. This graphical user interface (GUI) is designed for handling any type of input signal either in offline or online and gives more accurate results over conventional tool boxes. © 2012 IEEE.

关键词： Discrete wavelet transforms

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PATCH-BASED FEATURE MAPS FOR PIXEL-LEVEL image SEGMENTATION

PATCH-BASED FEATURE MAPS FOR PIXEL-LEVEL IMAGE SEGMENTATION

引用

20th European signal processing conference (EUSIPCO)

作者： Cao, Shuoying Iftikhar, Saadia Bharath, Anil Anthony Imperial Coll London London England

ISBN: (纸本)9781467310680

In this paper, we describe the use of phase-invariant complex wavelet filters, coupled to a training process involving a small, high-quality training dataset, to build an image segmentation system capable of performing in very low signal-to-noise, and under conditions of strong object-background contrast change. The three main components of our approach are: i) a patch-based feature description of local phase-invariant orientation fields;ii) a priori ground-truth data;iii) a machine learning method, such as Multilayer Perceptron (MLP) or kernel-based Support Vector Machine (SVM), to build an accurate classifier that is customised to the segmentation problem. A key feature of the approach is that it may be easily retrained and is, therefore, more adaptable to different imaging modalities. A representation of phase-invariant local image orientation using geometric algebra is first introduced;this is important to the patch-based approach. The quality of our trained systems is then assessed using Receiver Operating Characteristic (ROC) curves in two different biomedical applications: the human retinal vessel-bed in colour fundus images from the publicly available DRIVE database, and the rabbit endothelial cell boundaries of thoracic aorta microscopy images.

关键词： Segmentation visual features geometric algebra Multilayer Perceptron Support Vector Machine microscopy retinal imaging

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Radon transform and DWT based audio watermarking algorithm against DA/AD conversion

Radon transform and DWT based audio watermarking algorithm a...

引用

2012 3rd IEEE/IET International conference on Audio, Language and image processing, ICALIP 2012

作者： Li, Cairong Hu, Ruimin Zeng, Wei Faculty of History and Culture Hubei University China National Engineering Research Center for Multimedia Software Wuhan University China Jiangxi Electric Power Research Institute Nanchang China

ISBN: (纸本)9781467301718

Audio watermarking has become an important technology for the intellectual property protection. For numerous applications, such as cinema and concert situation, watermarks surviving noisy analog environments are better suited or even required. This paper discusses the robustness of digital audio watermarking algorithms against digital-to-analogue (D/A) and analogue-to-digital (A/D) conversions. Based on discrete wavelet decomposition, the chirp signal is introduced as watermarking bits and the radon transform of time-frequency distribution of wavelet coefficients is also considered. Then the relationship of statistical radon moment in two adjacent wavelet sub-bands is utilized to embed watermarking bits. Experimental results show that the proposed algorithm can resist on the attack of DA and AD conversion with lower bit error and higher capacity. The proposed method could also be against common signal processing and MPEG compression attack, which show its good prospect in real application. © 2012 IEEE.

关键词： wavelet decomposition

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Multispectral image fusion based on the multiwavelet and IHS transforms

Multispectral image fusion based on the multiwavelet and IHS...

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2012 20th signal processing and Communications applications conference, SIU 2012

作者： Nizam, Sema Telatar, Ziya Ankara Üniversitesi Mühendislik Fakültesi Elektronik Mühendisliǧi Bölümü Turkey

ISBN: (纸本)9781467300568

This paper introduces a fusion method to merge the IKONOS low resolution multispectral image (MS) with the IKONOS high resolution panchromatic (PAN) image based on the Multiwavelet transform. Different fusion rules are used with the Multiwavelet method to improve the fusion quality based on pixel level fusion or feature level fusion. The best three old techniques for image fusion (IHS, Brovey, and wavelet) are also tested in this paper. The performances of the existing and the proposed methods are calculated using Correlation Coefficient and Root Mean Square Error. Here we used our method to merge the panchromatic image of IKONOS sensor (1m resolution) with its multispectral image (4m resolution). Multiwavelet based image fusion method provides richer information in both spatial and spectral domains than the wavelet based method, and the results clearly demonstrate the advantages of this approach. © 2012 IEEE.

关键词： wavelet transforms

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