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Lung segmentation in pulmonary CT images using wavelet transform

Lung segmentation in pulmonary CT images using wavelet trans...

引用

32nd IEEE International conference on Acoustics, Speech and signal processing

作者： Talakoub, Omid Alirezaie, Javad Babyn, Paul Ryerson Univ Dept Elect & Comp Engn Toronto ON Canada Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada Univ Toronto Dept Med Imaging Toronto ON M5S 1A1 Canada

ISBN: (纸本)9781424407286

Computer-Aided Diagnosis (CAD) has become a major research interest in diagnostic radiology and medical imaging. The basic goal of CAD is to provide a computer output as a second opinion to assist medical image interpretation by improving accuracy, consistency of diagnosis, and image interpretation time. Since a CAD system is only interested in analyzing a specific organ, segmentation of Computer Tomography (CT) images is a precursor to most image analysis applications. A fully automated method is presented to segment lung in pulmonary CT images based on detected lung edges by wavelet analysis. Due to wavelet transformation characteristics, the proposed method is not only computational inexpensive compared to other existing methods such as snakes or watershed, but also is robust and accurate in detecting lung borders. A set of 330 low dose (50mA) CT images were processed demonstrating accuracy and satisfactory performance of the algorithm.

关键词： computer-aided diagnosis pulmonary CT images wavelet transformation segmentation edge detection

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Hypercomplete circular harmonic pyramids

Hypercomplete circular harmonic pyramids

引用

4th conference on wavelet applications in signal and image processing

作者： Jacovitti, G Manca, K Neri, K UNIV ROMA LA SAPIENZA DEPT INFO COMI-00184 ROMEITALY

ISBN: (纸本)0819422134

In this contribution we present a steerable pyramid based on a particular set of complex wavelets named circular harmonic wavelets (CHW). The proposed CHWs set constitutes a generalization of the smoothed edge wavelets introduced by Mallat, consisting of extending the local differential representation of a signal image from the first order to a generic n-th order. The key feature of the proposed representation is the use of complex operators leading to an expansion in series of polar separable complex functions, which are shown to possess the space-scale representability of the wavelets. The resulting tool is highly redundant, and for this reason is called hypercomplete circular harmonic pyramid (HCHP), but presents some interesting aspects in terms of flexibility, being suited for many image processing applications. In the present contribution the main theoretical aspects of the HCHPs are discussed along with some introductory applications.

关键词： Circular Harmonic wavelets multiscale image features analysis

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Enhancement of tropical land cover mapping with wavelet-based fusion and unsupervised clustering of SAR and landsat image data

Enhancement of tropical land cover mapping with wavelet-base...

引用

conference on image and signal processing for Remote Sensing vii

作者： Le Moigne, J Laporte, N Netanyahu, NS NASA Goddard Space Flight Ctr Appl Informat Sci Branch Greenbelt MD 20771 USA

ISBN: (纸本)0819442666

The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument. In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

关键词： image fusion land cover mapping wavelet representation unsupervised clustering remote sensing imagery

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Single image Ear Recognition Using wavelet-Based Multi-Band PCA 27

Single Image Ear Recognition Using Wavelet-Based Multi-Band ...

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27th European signal processing conference (EUSIPCO)

作者： Zarachoff, Matthew Sheikh-Akbari, Akbar Monekosso, Dorothy Leeds Beckett Univ Sch Comp Creat Technol & Engn Leeds W Yorkshire England

ISBN: (纸本)9789082797039

Principal Component Analysis (PCA) has been successfully used for many applications, including ear recognition. This paper presents a 2D wavelet based Multi-Band PCA (2D-WMBPCA) method, inspired by PCA based techniques for multispectral and hyperspectral images, which have shown a significantly higher performance to that of standard PCA. The proposed method performs 2D non-decimated wavelet transform on the input image dividing the image into its subbands. It then splits each resulting subband into a number of bands evenly based on the coefficient values. Standard PCA is then applied on each resulting set of bands to extract the subbands eigenvectors, which are used as features for matching. Experimental results on images of two benchmark ear image datasets show that the proposed 2D-WMBPCA significantly outperforms both the standard PCA method and the eigenfaces method.

关键词： Ear recognition principal component analysis multi-band image creation non-decimated wavelet transform

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SPARSE BASED image COMPRESSION IN wavelet DOMAIN

SPARSE BASED IMAGE COMPRESSION IN WAVELET DOMAIN

引用

IEEE International conference on signal processing and Communication (ICSPC)

作者： Ashwini, K. Amutha, R. Harini, K. SSN Coll Engn Dept ECE Chennai Tamil Nadu India

ISBN: (纸本)9781509067305

Sparse representation techniques have been found to provide improved results in many signaling and imaging applications. Especially in the field of image compression, this technique is able to compress the images with higher compression ratio and is also able to retrieve back the compressed image with good quality and resolution. In this paper, wavelet and Sparse based image compression technique is presented. Using Discrete wavelet Transform (DWT), the image to be compressed is initially decomposed into approximation and detail coefficients. The approximation coefficients are encoded directly with lossless encoding technique. In the case of detailed coefficients, their sparse representations are obtained using learned dictionary and these sparse vectors are quantized and encoded. Inverse discrete wavelet transform (IDWT) is applied with the estimated detail and approximation coefficients at the decompression stage, to retrieve back the decompressed image. They key issue of learning appropriate dictionaries for obtaining the sparse vectors is addressed in this paper. The proposed algorithm is tested on several standard test images and has been validated with popular metrics namely Peak signal to noise ratio (PSNR), Structural similarity index (SSIM) and Correlation coefficient.

关键词： Sparse representation DWT IDWT Dictionary

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Empirical Modal Decomposition applied to cardiac signals analysis

Empirical Modal Decomposition applied to cardiac signals ana...

引用

conference on wavelet applications in Industrial processing vii

作者： Beya, O. Jalil, B. Fauvet, E. Laligant, O. CNRS LE2I IUT UMR 5185 F-71200 Le Creusot France

ISBN: (纸本)9780819479280

In this article, we present the method of empirical modal decomposition (EMD) applied to the electrocardiograms and phonocardiograms signals analysis and denoising. The objective of this work is to detect automatically cardiac anomalies of a patient. As these anomalies are localized in time, therefore the localization of all the events should be preserved precisely. The methods based on the Fourier Transform (TFD) lose the localization property [13] and in the case of wavelet Transform (WT) which makes possible to overcome the problem of localization, but the interpretation remains still difficult to characterize the signal precisely. In this work we propose to apply the EMD (Empirical Modal Decomposition) which have very significant properties on pseudo periodic signals. The second section describes the algorithm of EMD. In the third part we present the result obtained on Phonocardiograms (PCG) and on Electrocardiograms (ECG) test signals. The analysis and the interpretation of these signals are given in this same section. Finally, we introduce an adaptation of the EMD algorithm which seems to be very efficient for denoising. Lastly, prospects and a conclusion complete this work.

关键词： EMD Phonocardiograms Electrocardiograms signal processing

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CFAR-enhanced image codec for SONAR ATR

CFAR-enhanced image codec for SONAR ATR

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Proceedings of the 1999 wavelet applications in signal and image processing vii

作者： Tian, Jun Wells Jr., Raymond O. Rice Univ Houston United States

The wavelet transform gives a compact multiscale representation of a digital image and provides a hierarchical structure which is well suited for post-processing. With its good localization property in both the spatial domain and the frequency domain, wavelet-based image compression has gained a huge success in the past several years. In this paper we present a wavelet-based image codec specially designed for an automatic target recognition (ATR) system. Due to the large amount of data size, a 'good' image compression algorithm is both necessary and important as a pre-processing stage for an ATR system, especially in a 'real-time' processing situation. We incorporate a constant false alarm rate (CFAR) detector into an embedded image compression algorithm to efficiently code target pixels exclusively in the bit stream. The new image codec, which is enhanced by the CFAR feature, clearly exhibits (potential) targets in the decompressed image. Another new feature of this codec is a wavelet-interpretation of the CFAR detector, a multiscale representation of the CFAR values in the wavelet domain.

关键词： wavelet transforms

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Identification of Acrylamide in Fried Potato Crisps Using image processing in wavelet Domain 38

Identification of Acrylamide in Fried Potato Crisps Using Im...

引用

38th International conference on Telecommunications and signal processing (TSP)

作者： Singh, Anushikha Dutta, Malay Kishore Burget, Radim Masek, Jan Amity Univ Sect 125 Noida Uttar Pradesh India Brno Univ Technol Fac Elect Engn CS-61090 Brno Czech Republic

ISBN: (纸本)9781479984985

Acrylamide is a toxic carcinogenic material that commonly occurs in heated starchy food items like potato crisps. Identification of such toxic chemical in food items using conventional chemical laboratory based methods is time consuming and expensive and may need specialized manpower for such laboratory testing. This paper proposes an efficient image processing based non-destructive testing method for identification of acrylamide in potato crisps. The image of the potato crisps is automatically segmented and features are extracted from the images in wavelet domain. These features are then analyzed for identification of the presence of acrylamide in these samples. The variation in the various features of the image is related to the presence of acrylamide. The experimental results indicate that the proposed method is efficient for identification of acrylamide from the wavelet features of the images. The proposed method achieves 90% of accuracy and it can be used for real time applications.

关键词： Toxic substances Acrylamide image processing Feature Extraction Discrete wavelet Transform

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Integrated wavelets for medical image analysis

Integrated wavelets for medical image analysis

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wavelets - applications in signal and image processing X conference

作者： Heinlein, P Schneider, W ImageDiagnost GmbH D-85375 Munich Germany

ISBN: (纸本)0819450804

Integrated wavelets are a new method for discretizing the continuous wavelet transform (CWT). Independent of the choice of discrete scale and orientation parameters they yield tight families of convolution operators. Thus these families can easily be adapted to specific problems. After presenting the fundamental ideas, we focus primarily on the construction of directional integrated wavelets and their application to medical images. We state an exact algorithm for implementing this transform and present applications from the field of digital mammography. The first application covers the enhancement of microcalcifications in digital mammograms. Further, we exploit the directional information provided by integrated wavelets for better separation of microcalcifications from similar structures.

关键词： integrated wavelet continuous wavelet transform scale-angle digital mammography

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Fidelity and robustness analysis of image adaptive DWT-based watermarking schemes

Fidelity and robustness analysis of image adaptive DWT-based...

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SIGMAP 2007 - International conference on signal processing and Multimedia applications

作者： Colle, Franco Del Gómez, Juan Carlos Laboratory for System Dynamics and Signal Processing FCEIA Universidad Nacional de Rosario Argentina

An image Adaptive Watermarking method based on the Discrete wavelet Transform is presented in this paper. The robustness and fidelity of the proposed method are evaluated and the method is compared to state-of-the-art watermarking techniques available in the literature. For the evaluation of watermark transparency, an image fidelity factor based on a perceptual distortion metric is introduced. This new metric allows a perceptually aware objective quantification of image fidelity.

关键词： Discrete wavelet transforms

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