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共 3114 条记录，以下是361-370 订阅

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Adaptive Multiple Description Depth image Coding Based on wavelet Sub-band Coefficients 13th

Adaptive Multiple Description Depth Image Coding Based on Wa...

引用

13th International conference on Intelligent Information Hiding and Multimedia signal processing (iiH-MSP)

作者： Ma, Jingyuan Bai, Huihui Liu, Meiqin Chang, Dongxia Ni, Rongrong Zhao, Yao Beijing Jiaotong Univ Inst Informat Sci Beijing 100044 Peoples R China

ISBN: (纸本)9783319638591;9783319638584

With the development of multi-view video plus depth technology, the coding algorithm at the depth image has become one of hot research directions. As we know, after wavelet transform, the energy of the image smoothing region is concentrated in low frequency sub-band, while the edge information of the texture region is concentrated in high frequency sub-bands. However, the edge information is very important to the synthetic viewpoint. In order to improve the edge decoding quality and ensure the transmission reliability, we propose an adaptive multiple description depth image coding scheme based on wavelet sub-band coefficients. The low frequency sub-band is encoded by optimized multiple description lattice quantization (OMDLVQ), while the high frequency sub-bands are encoded by embedded block coding with dead-zone. Finally, two streams of the vector quantization are combined with the embedded block coding stream respectively. The experimental results show that this scheme has good performance in transmission reliability and reconstructed image quality.

关键词： Depth image wavelet transform MDLVQ SPECK

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Robust Face Recognition Approaches Using PCA, ICA, LDA Based on DWT, and SVM algorithms 41

Robust Face Recognition Approaches Using PCA, ICA, LDA Based...

引用

41st International conference on Telecommunications and signal processing (TSP)

作者： Lahaw, Zied Bannour Essaidani, Dhekra Seddik, Hassene ENSIT Prod Res Ctr CEREP 5 Av Taha Hussein Tunis 1008 Tunisia

ISBN: (纸本)9781538646953

Face Recognition represents one of the attracting research areas. It has drawn the attention of many researchers due to its varying applications such as database identification, identity authentication, surveillance and security access control human computer interaction.... In this order, different face recognition algorithms are proposed. These methods are based on the face representations. In order to use the most important information in the face representation, we propose to exploit the concept of 2D-DWT for the image compression as a pre-processing for feature extraction. In fact, the DWT is performed at different scales and orientations so it is sensitive to strong lighting conditions and facial details. Based on the DWT advantages, the LL sub-band of the processed image is used as input image for feature extraction process based on ICA, PCA, LDA and SVM algorithms. The importance of the proposed approaches is evaluated by experimental and comparative studies tested on AT&T database.

关键词： Face Recognition Discrete wavelet Transform Principal Component Analysis Linear Discriminant Analysis Independent Component Analysis Support Vector Machine

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A new objective metric to predict image quality using deep neural networks 41

A new objective metric to predict image quality using deep n...

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conference on applications of Digital image processing XLI

作者： Akyazi, Pinar Ebrahimi, Touradj Ecole Polytech Fed Lausanne Multimedia Signal Proc Grp MMSPG CH-1015 Lausanne Switzerland

ISBN: (数字)9781510620766

ISBN: (纸本)9781510620766

Quality assessment of images is of key importance for mulmedia applications. In this paper we present a new full reference objective metric to predict the quality of images using deep neural networks. The network makes use of both the color as well as frequency information extracted from reference and distorted images. Our method comprises of extracting a number of equal sized random patches from the reference image and the corresponding patches from the distorted image, then feeding the patches themselves as well as their 3-scale wavelet transform coe ffi cients as input to a neural network. The architecture of the network consists of four branches, with the fi rst three generating frequency features and the fourth extracting color features. Feature extraction is carried out using 12 to 15 convolutional layers and one pooling layer, while two fully connected layers are used for regression. The overall image quality is computed as a weighted sum of patch scores, where local weights are also learned by the network using two additional fully connected layers. The network was trained using TID2013 and tested on TID2013, CSIQ and LIVE image databases. Our results show high correlations with subjective test scores, are generalizable for certain types of distortions and are competitive with respect to the state-of-the-art methods.

关键词： Objective image quality assessment full reference image quality metric deep convolutional neural networks discrete wavelet transform

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A Comparative Analysis of Clustering Algorithms for Ultrasound image Despeckling applications 18

A Comparative Analysis of Clustering Algorithms for Ultrasou...

引用

2nd International conference on Graphics and signal Proceesing (ICGSP)

作者： Singh, Prerna Mukundan, Ramakrishnan de Ryke, Rex Univ Canterbury Dept Comp Sci & Software Engn Christchurch New Zealand Canterbury Dist Hlth Board Radiol Serv Christchurch New Zealand

ISBN: (纸本)9781450363860

This paper proposes a novel framework for speckle noise suppression and edge preservation using clustering algorithms in ultrasound images. The algorithms considered are K-means clustering, fuzzy C-means clustering, possibilistic C-means, fuzzy possibilistic C-means, and possibilistic fuzzy C-means clustering. This work presents an exhaustive comparative analysis of the above clustering algorithms to consider their suitability for despeckling and identifies the best clustering algorithm. Two types of dataset are considered: medical ultrasound images of the thyroid, and synthetically modelled ultrasound images. The framework consists of several distinct phases - first the edges of the image are identified using the Canny edge operator, and then a clustering algorithm applied on high frequency coefficients extracted using wavelet transform. Finally, the preserved edges are added back to speckle suppressed image. Thus, the proposed clustering method effectively accomplishes both speckle suppression and edge preservation. This paper also presents a quantitative evaluation of results to demonstrate the effectiveness of the clustering approach.

关键词： Ultrasound image analysis speckle noise wavelet transform Canny edge detector Clustering algorithms image quality metrics

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Fractal image processing and Analysis for Compression of Hyperspectral images

Fractal Image Processing and Analysis for Compression of Hyp...

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International conference on Computing and Networking Technology (ICCNT)

作者： Tripty Singh Tina Babu Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

Hyperspectral imaging is a technique in which the information is collecting and processing across an electromagnetic spectrum. Fractal image processing deals with various dimensions of an image. Hyperspectral analysis are applied on multiple frequency bands of images, and produces spatial and spectral information. HSI can elongate 390 to 700 nm i.e UV to infrared and near-infrared wavelength regions. This technique based system engenders narrow band() images of different wavelengths. By utilizing HIS, visualization can be elongated to invisible wavelengths. Hyperspectral based techniques have applications in various fields such as medical diagnosis, agriculture, food processing, remote sensing etc. In this project, the compression of hyperspectral images is considered. Present work involves Modified DCT-Discrete Cosine Transformation based image compression. Compared with the convention lossless compression techniques of the benchmark multi-component and hyperspectral (JPEG2000), the MOD-DCT lossless algorithm produces considerable reduce in compressed file size for beyond visible range. After implementation of Modified DCT for hyperspectral images high compression ratio was achieved.

关键词： image coding Hyperspectral imaging Discrete cosine transforms Quantization (signal) Fractals wavelet domain

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image Compression using 2D-Discrete wavelet Transform on a Light-Weight Reconfigurable Hardware 31

Image Compression using 2D-Discrete Wavelet Transform on a L...

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31st International conference on VLSI Design / 17th International conference on Embedded Systems (VLSID & ES))

作者： Jain, Nupur Singh, Mansi Mishra, Biswajit Dhirubhai Ambani Inst Informat & Commun Technol VLSI Gandhinagar 382007 Gujarat India Dhirubhai Ambani Inst Informat & Commun Technol Embedded Syst Res Grp Gandhinagar 382007 Gujarat India

ISBN: (纸本)9781538636923

This paper presents a hardware implementation of a 2D-DWT on a reconfigurable architecture targeting image processing applications. The architecture is capable of performing various other digital signal and image processing functions such as CORDIC, FIR filtering, 2D convolution and DCT to compute transforms, trigonometric functions etc. In this paper, we present the mapping of a configurable 2D-DWT algorithm using convolution method with separable filter approach having filter length upto 8 taps on the reconfigurable architecture hardware. The reconfigurable hardware architecture mapped with 2D-DWT is ported onto an FPGA that has a frequency of operation of 37.26 MHz. For a 1-level decomposition, the number of clock cycles are 496 per 8x8 block of the NxN image with a total clock cycles equals 31N(2)/4 with 75% compression and can be further improved by computing higher levels of decomposition of the 2D-DWT.

关键词： 2D-DWT image processing Reconfigurable Hardware wavelets

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Multi-Rate signal processing with the Use of Filter Banks Composed of Parallel FIR Filters

Multi-Rate Signal Processing with the Use of Filter Banks Co...

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International conference on Microelectronics, MIEL

作者： M. Banach R. Długosz Poznan University of Technology Institute of Architecture and Spatial Planning Nieszawska 13C Poznań Poland Aptiv Services Poland ul. Podgórki Tynieckie 2 Kraków Poland

The paper presents a concept of a hardware implementation of 2-D finite impulse response (FIR) filter banks for the application in image processing and analysis. Banks composed of low-and high-pass FIR filters are basic components of multi-stage discrete wavelet transform (DWT). The applications of such solutions that are in the scope of our interests are vision systems used in automotive active safety functions (e.g in line departure warning). Basics of the DWT are broadly described in the literature. In our work we focus on solutions supporting hardware realization of filter banks for DWT. The proposed parallel and asynchronous circuits allow to achieve the processing time for a single pixel not exceeding 2 to 4 ns, depending on the size of the mask (data for TSMC 180 nm CMOS process).

关键词： Discrete wavelet transforms Finite impulse response filters Hardware Frequency response Complexity theory

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Adaptive PET/CT fusion using empirical wavelet transform 2nd

Adaptive PET/CT fusion using empirical wavelet transform

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2nd International conference on Computational Intelligence and Informatics, ICCii 2017

作者： Barani, R. Sumathi, M. V.V.Vanniaperumal College for Women VirudhunagarTamil Nadu626001 India Sri Meenakshi Government Arts College for Women MaduraiTamil Nadu625021 India

ISBN: (纸本)9789811082276

Empirical wavelet Transform (EWT) is an adaptive signal decomposition technique in which the wavelet basis is constructed based on the information contained in the signal instead of a fixed basis as in standard wavelet Transform (WT). Its adaptive nature enables EWT in many image processing applications like image denoising, image compression, etc. In this paper, a new adaptive image fusion algorithm is proposed for combining CT and PET images using EWT. EWT first decomposes both the images into approximate and detailed components using the adaptive filters that are constructed according to the content of an image by estimating the frequency boundaries. Then, the corresponding approximate and detailed components of CT and PET images are combined by using appropriate fusion rules. An adaptive EWT image fusion, a newly proposed method, is compared with standard WT fusion using the image quality metrics, image fusion metrics and error metrics. The quantitative analysis proved that the newly proposed method results in better quality than the standard WT method. © 2018, Springer Nature Singapore Pte Ltd.

关键词： image fusion

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Lenslet Light Field Imaging Scalable Coding 26

Lenslet Light Field Imaging Scalable Coding

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26th European signal processing conference (EUSIPCO)

作者： Garrote, Joao Brites, Catarina Ascenso, Joao Pereira, Fernando Univ Lisbon Inst Telecomunicacoes Inst Super Tecn Av Rovisco Pais P-1049001 Lisbon Portugal

ISBN: (纸本)9789082797015

Light fields have emerged as one of the most promising 3D representation formats, enabling a richer and more immersive representation of a visual scene. The lenslet light field acquisition approach consists in placing an array of micro-lenses between the camera main lens and the photosensor to allow capturing both the intensity and the direction of the light rays. This type of representation format offers new interaction possibilities with the visual content, notably a posteriori refocusing and visualization of different perspectives of the visual scene. However, this representation model is associated to very large amounts of data, thus requiring efficient coding solutions in order applications involving storage and transmission may be deployed. This paper proposes a novel lenslet light field imaging scalable coding solution adopting a wavelet-based approach, able to offer view, quality and spatial scalabilities, to meet the characteristics of multiple types of displays, transmission channels and user needs. The performance results show that the proposed coding solution performs better than alternative scalable coding solutions, notably JPEG 2000.

关键词： lenslet light field sub-aperture image disparity estimation and compensation scalability JPEG 2000

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A Novel Incremental Face Recognition Method Based on Nonparametric Discriminant Model 4

A Novel Incremental Face Recognition Method Based on Nonpara...

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4th International conference on Advanced Technologies for signal and image processing (ATSIP)

作者： Soula, Arbia Ben Said, Salma Ksantini, Riadh Lachiri, Zied Univ Tunis El Manar Signal Images & Informat Technol LR SITI ENIT Tunis Tunisia Univ Tunis El Manar Signal Images & Informat Technol LR SITI ENIT INSAT Tunis Tunisia Univ Windsor Windsor ON Canada SUPCOM Secur Numer Ariana Tunisia Univ Tunis El Manar ENIT Res Lab SITI Elect Engn Dept Tunis Tunisia

ISBN: (纸本)9781538652398

Face recognition has received considerable interest owing to its relevance in several domains. Yet, it has some difficulties in many real world applications, where data are collected continuously and must be updated over time. In the present, we advance an adept face recognition technique that rests on Incremental Nonparametric Discriminant Analysis (INDA). We use the Gabor wavelet to extract facial features on which multi-lob ordinal filter are applied to derive Ordinal measures that are encoded in local zones, as visual parameters. Then, the statistical dispersion of these parameters is integrated to get a feature vector whose dimension is decreased by making use of PCA and variance. Last but not least, every single feature vector is treated as a feature input for the INDA. The proffered face recognition technique was assessed on the well-known ORL and Yale face databases. Experimental results have shown clearly its superiority and skillfulness in terms of recognition performance.

关键词： incremental learning nonparametric discriminant analysis Gabor filter face recognition

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