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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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Reconfigurable Computing for Imaging Systems

Reconfigurable Computing for Imaging Systems

引用

International conference on image processing Theory, Tools and applications (IPTA)

作者： Amira, Abbes Univ West Scotland Paisleyc England

ISBN: (纸本)9781479964635

Summary form only given. This talk will address different software and hardware issues related to the design and implementation of imaging systems using reconfigurable computing. A range of algorithms, including discrete wavelet transform (DWT), Ridgelet and Curvelet transforms will be presented for imaging applications such as medical image denoising, segmentation and compression and biometrics. The implementation process of these algorithms on Field Programmable Gate Arrays (FPGAs) will be described. In addition, the talk will review the latest reconfigurable hardware technologies and development methods for real-time embedded systems, and will conclude with comprehensive case studies demonstrating the deployment of low power reconfigurable architectures for algorithms acceleration and performance evaluation methods for reconfigurable imaging systems.

关键词： curvelet transforms discrete wavelet transforms embedded systems field programmable gate arrays image processing reconfigurable architectures DWT FPGA Ridgelet transforms biometrics discrete wavelet transform hardware issues imaging applications low power reconfigurable architectures medical image compression medical image denoising medical image segmentation real-time embedded systems reconfigurable computing reconfigurable hardware technologies reconfigurable imaging systems software issues Algorithm design and analysis Biometrics (access control) Educational institutions Field programmable gate arrays Hardware Imaging signal processing algorithms Field programmable gate arrays wavelet Analysis discrete wavelet transform Algorithm design and analysis Reconfigurable architectures signal processing algorithms Biometrics Educational institutions Embedded systems Computer hardware image denoising Imaging systems image processing

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Color image Compression Based on wavelet Transform and Support Vector Regression WSVR for Color image Compression 1

Color Image Compression Based on Wavelet Transform and Suppo...

引用

conference on First International image processing, applications and Systems

作者： Zikiou, Nadia Lahdir, Mourad Ameur, Soltane Univ Mouloud Mammeri UMMTO Dept Elect LAMPA Tizi Ouzou Algeria

ISBN: (纸本)9781479970698

Recent years have seen tremendous increase in the production, transportation and storage of color images. A new method for loss less image compression of color images is presented in this paper. This method is based on wavelet transform and support vector machines (SVM). The wavelet transform is applied to the luminance (Y) and chrominance (Cb, Cr) components of the original color image. Then SVM regression dependence could learn from training data and compression achieved using less training point (support vector) to represent the original data and eliminate redundancy. In addition, an effective entropy coder based on run-length and arithmetic encoders is used to encode vector and weight support. Our compression algorithm is applied to a test set of images of size 1024 * 1024 encoded on 24 bits. To evaluate our results, we calculated the peak signal noise ratio (PSNR) and their ratios datasets compression (CR). Experimental results show that the performance of the compression algorithm to achieve much improvement.

关键词： Color image compression wavelet Transform Support Vector Regression (SVR) Run-length Arithmetic coding PSNR

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On sensitivity of texture parameters to smooth variations of local image intensity and contrast 18

On sensitivity of texture parameters to smooth variations of...

引用

18th IEEE conference on signal processing - Algorithms, Architectures, Arrangements, and applications (SPA)

作者： Strzelecki, Michal Materka, Andrzej Lodz Univ Technol Inst Elect Lodz Poland

ISBN: (纸本)9788362065189

Nonuniformities in illumination of a scene and/or in imaging device response can deteriorate texture analysis results since some texture parameters depend not only on the properties of visualized structure but also on local mean and variance of the image. This work is an attempt to discuss the sensitivity of texture parameters to image inhomogeneities (non uniformities) to select those which do not alter their values significantly. The properties of widely used texture parameters, i.e. based on gray level co-occurrence matrix, run length matrix and wavelet transform are taken into account. Two nonuniformity models are considered: smooth variations of image intensity and of its contrast, respectively. The discussion is illustrated by classification examples performed for natural textures from the Brodatz album. In conclusion, some features are identified, which represent certain immunity to the discussed image inhomogeneities.

关键词： texture analysis image inhomogeneity texture parameters sensitivity

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Glaucomatous image Classification using wavelet Transform

Glaucomatous Image Classification using Wavelet Transform

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International conference on Advanced Communication Control and Computing Technologies*

作者： Rajan, A. Ramesh, G. P. Yuvaraj, J. St Peters Univ Dept ECE Chennai Tamil Nadu India Shri Andal Alagar Coll Engn Mamandur India

ISBN: (纸本)9781479939145

wavelet Transforms is a part of large community of mathematical function approximation method, they are being increasing and being deployed in image processing for segmentation, filtering, classification etc. This work is based on image classification with the use of single level Discrete wavelet Transform (DWT). wavelets have been employed in many applications of signal processing. The texture features within images are extracted for accurate and efficient Glaucoma Classification. Energy is distributed over the wavelet sub-bands to find these important texture features. The discriminatory potential of wavelet features obtained from the daubechies (db3), symlets (sym3), and reverse biorthogonal (rbio3.3, rbio3.5, and rbio3.7) wavelet filters. We propose a technique to extract energy features obtained using 2-D discrete wavelet transform. The energy features obtained from the detailed coefficients can be used to distinguish between normal and glaucomatous images with very high accuracy. The effectiveness is evaluated using K-NN classifier by taking 30 normal and glaucoma images, 15 images are used for training and 15 images for testing.

关键词： Biomedical optical imaging feature extraction glaucoma image texture wavelet transforms

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Watermarking For Depth Map Based 3D images Using wavelet Transform 3

Watermarking For Depth Map Based 3D Images Using Wavelet Tra...

引用

3rd International conference on Communications and signal processing (ICCSP)

作者： Jaipuria, Smita Jagdishprasad JSCOE Dept Elect & Telecommun Pune Maharashtra India

ISBN: (纸本)9781479933587

3D content protection, Effective digital watermarking systems will play a very important role for promoting and developing the 3D entertainment industry. 3D images are used widely in medical imaging, virtual reality, computer aided design and video games. Recently, different types of 3D applications and the uses of 3D content are growing up, with the emerging of low cost 3D display devices. The main aim of this project is to present the efficient and robust watermarking scheme for Depth Map Based 3D images. This method called depth-image-based rendering (DIBR). To present the new system framework for proposed 3D image watermarking approach. This paper focuses on the advantages of this new approach on 3D TV. In this paper, we propose a robust watermarking scheme for DIBR 3D images by quantization on wavelet transform coefficients with consideration of imperceptibility. Watermarking scheme is proposed for the content protection problem of DIBR 3D images.

关键词： 3D images digital watermarking DIBR (depth image based rendering) wavelet transform

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CHANGE DETECTION ON SAR imageS USING DIVISIVE NORMALIZATION-BASED image REPRESENTATION

CHANGE DETECTION ON SAR IMAGES USING DIVISIVE NORMALIZATION-...

引用

IEEE International conference on Acoustics, Speech and signal processing (ICASSP)

作者： Xu, Qian Karam, Lina J. Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85004 USA

ISBN: (纸本)9781479928934

In the context of multi-temporal synthetic aperture radar (SAR) images for earth monitoring applications, one critical issue is the detection of changes occurring after a natural or anthropic disaster. In this paper, we propose a new similarity measure for automatic change detection based on a divisive normalization image representation. The divisive normalization transform (DNT) has been recognized as a successful methodology to model the perceptual sensitivity of biological vision and a useful image representation that significantly reduces statistical dependence of natural images. In this work, we exploit the fact that the histogram of DNT coefficients within wavelet subbands can often be well fitted with a zero-mean Gaussian density function, which is a one-parameter function that allows efficient change detection of SAR images. The proposed change detector is compared to other recent model-based approaches. Tests on real data show that our detector outperforms previously suggested methods in terms of the rate of false alarm rate and the total error rate.

关键词： change detection Divisive normalization Gaussian scale mixture synthetic aperture radar (SAR) images

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Saliency guided wavelet compression for low-bitrate image and Video coding

Saliency guided Wavelet compression for low-bitrate Image an...

引用

IEEE Global conference on signal and Information processing

作者： Souptik Barua Kaushik Mitra Ashok Veeraraghavan Rice University USA Indian Institute of Technology Madras India

ISBN: (纸本)9781479975921

We propose an improved saliency guided wavelet compression scheme for low-bitrate image/video coding applications. Important regions (faces in security camera feeds, vehicles in traffic surveillance) get degraded significantly at low bitrates by existing compression standards, such as JPEG/JPEG-2000/MPEG-4, since these do not explicitly utilize any knowledge of which regions are salient. We design a compression algorithm which, given an image/video and a saliency value for each pixel, computes a corresponding saliency value in the wavelet transform domain. Our algorithm ensures wavelet coefficients representing salient regions have a high saliency value. The coefficients are transmitted in decreasing order of their saliency. This allows important regions in the image/video to have high fidelity even at very low bitrates. Further, our compression scheme can handle several salient regions with different relative importance. We compare the performance of our method with the JPEG/JPEG-2000 image standards and the MPEG-4 video standard through two experiments: face detection and vehicle tracking. We show improved detection rates and quality of reconstructed images/videos using our Saliency Based Compression (SBC) algorithm.

关键词： Saliency wavelet transform image coding Video coding

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An Improved Dual Tree Complex wavelet Transform based image denoising using GCV thresholding 1

An Improved Dual Tree Complex Wavelet Transform based Image ...

引用

First International conference on Computational Systems and Communications (ICCSC)

作者： Varsha, A. Basu, Preetha TKM Coll Engn Dept Elect & Commun Engn Kollam Kerala India

ISBN: (纸本)9781479960132

Noise suppression is an integral part of any image processing task. Noise significantly degrades the image quality and hence makes it difficult for the observer to discriminate fine detail of the images especially in diagnostic examinations. Through decades of research, mass articles on image denoising have been proposed. The effect of noise in the images can be reduced by using either spatial filtering or transform domain filtering. In transform domain wavelet method provide better de-noising while preserving the details of images like edges. The Discrete wavelet Transform (DWT) has some disadvantages that undetermined its application in image processing as lack of shift invariance and poor directional selectivity. In order to overcome these disadvantages Dual Tree Complex wavelet Transform (DT-CWT) is used which provide perfect reconstruction over the traditional wavelet transform. It employs 2 real DWTs;the first DWT gives the real part of the transform while second DWT gives the imaginary part. It is nearly shift invariant and directionally selective in two and higher dimensions with limited redundancy. The DTCWT outperforms the DWT for applications like image de-noising and enhancement. One of the advantages of the DTCWT is that it can be used to implement 2D wavelet transforms that are more selective with respect to orientation than is the 2D DWT. The 2D DTCWT produces twelve sub bands at each scale, each of which are strongly oriented at distinct angles. A Dual Tree Complex wavelet transform based image denoising is proposed which uses generalized cross validation technique. The denoising performance for different images using Discrete wavelet Transform and Dual Tree Complex wavelet transform with different thresholding need to be evaluated. Evaluation is carried out in terms of various parameters such as Peak signal to Noise Ratio, mean Structural Similarity and Coefficient of Correlation.

关键词： image wavelet transform complex wavelets noise dwt denoising dtcwt psnr threshold

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Visually Significant Feature Point Maps for image Retrieval applications

Visually Significant Feature Point Maps for Image Retrieval ...

引用

1st International conference on signal processing and Integrated Networks (SPIN)

作者： Sarathi, M. Partha Ansari, M. A. Amity Univ ASET ECE dept Greater Noida India

ISBN: (纸本)9781479928668

In this paper, we propose a hybrid feature point detector based on a fusion of a multi-scale edge map and a wavelet based interest point representation. The feature points thus obtained are used for efficient image indexing and retrieval. Proposed method preserves an optimum number of significant feature points. Our method is compared against other existing interest point detectors. Efficacy of the proposed method is evaluated via a image retrieval system against the standard test databases. A similarity distance measure like Hausdorff distance is used for image matching, indexing and ranking of results considering the spatial information of the local structures in the image.

关键词： wavelets Canny edge feature points Hausdorff distance Retrieval

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Multilevel-DWT based image De-noising using Feed Forward Artificial Neural Network

Multilevel-DWT based Image De-noising using Feed Forward Art...

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1st International conference on signal processing and Integrated Networks (SPIN)

作者： Saikia, Torali Sarma, Kandarpa Kumar Gauhati Univ Dept Elect & Commun Engn Gauhati 781014 Assam India

ISBN: (纸本)9781479928668

It is seen that during image acquisition, storage, retrieval or transmission, images get degraded due to presence of noise. With different varieties of noise and its extent, de-noising becomes challenging. Traditionally, a host of techniques have considered spatial, statistical and multiple domain approaches for de-noising. Yet, the scope always exist for exploring innovative means of performing de-noising for enhancing image quality. In the proposed work, we present an approach to de-noise images by combining the features of multilevel Discrete wavelet Transform (DWT) and Feed Forward Artificial Neural Network (FF ANN). We apply our algorithm to de-noise the images corrupted by a kind of multiplicative noise known as speckle noise. The results show that the proposed method proves effective for a range of variations and is suitable for critical applications.

关键词： Noise de-noising Multilevel Discrete wavelet Transform (DWT) Feed Forward Artificial Neural Network (FF ANN)

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