检索结果-内蒙古大学图书馆

image denoising using 2-D separable oversampled DFT modulated filter banks

IET image processing 2009年第3期3卷 163-173页

作者： Shui, P. -L. Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

The direction-frequency selectivity of two-dimensional (2-D) separable oversampled discrete Fourier transform (DFT) modulated filter banks, showing that such 2-D filter banks can provide. ne frequency tiling and efficient image representations with direction-frequency selectivity, is analysed. Moreover, the doubly local Wiener filtering is extended to the case using two 2-D separable oversampled DFT modulated filter banks, where the empirical subband energy distributions of the image are estimated by the two sets of directional windows matching the direction-frequency selectivity of the subband filters. The proposed algorithm is of low computational complexity and exhibits a great capability to preserve inhomogeneous textures, owing to the fact that 2-D separable DFT modulated bases are suited to represent oscillating patterns in images. The experimental results show that the proposed denoising algorithm is competitive with the existing algorithms with comparable computational complexity. Particularly, for images with abundant inhomogenous texture, it gives larger output peak signal-to-noise ratios (PSNRs) and achieves better visual effect in texture regions of images.

关键词： image representation direction-frequency selectivity scheme Filtering methods in signal processing image sampling computer vision and image processing techniques discrete Fourier transforms channel bank filters Optical, image and video signal processing Integral transforms Wiener filters directional window matching method discrete Fourier transform image texture 2D separable oversampled DFT modulated filter bank image denoising computational complexity Wiener filtering subband energy distribution scheme

来源：评论

学校读者我要写书评

暂无评论

A modified 3D EfficientNet for the classification of Alzheimer's disease using structural magnetic resonance images

引用

IET image processing 2023年第1期17卷 77-87页

作者： Zheng, Bowen Gao, Ang Huang, Xiaona Li, Yuhan Liang, Dong Long, Xiaojing Chinese Acad Sci Shenzhen Inst Adv Technol Res Ctr Med AI Shenzhen Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

Structural magnetic resonance imaging (MRI) provides useful information for biomarker exploration and intelligent classification of Alzheimer's disease (AD). Machine learning and deep learning methods have been used in feature extraction and computer-aided diagnosis or prediction of AD. In this research, a new deep learning model is developed to detect or predict AD in an effective manner. A modified 3D EfficientNet with a sequentially connected 3D mobile inverted bottleneck convolution (MBConv) block is proposed to explore the multiscale characteristics of brain MR images for AD classification. The 3D MBConv block consists of depthwise convolution and a squeeze-and-excitation module to transform the input features into more compact features with fewer parameters than those in standard convolution. The proposed method was evaluated considering four classification tasks: (1) NC versus AD, (2) NC versus all MCI, (3) NC versus pMCI, and (4) sMCI versus pMCI. The proposed model achieved accuracies of 95.00%, 86.67%, and 83.33% for the classification of NC versus AD, NC versus pMCI, and sMCI versus pMCI, respectively, and exhibited a high performance in comparison with the classical networks and several existing methods. Efficient deep learning networks are powerful tools for the early diagnosis and prediction of AD.

关键词： biomarker exploration Biology and medical computing feature extraction structural magnetic resonance imaging brain MR images diseases image classification AD classification biomedical MRI Medical magnetic resonance imaging and spectroscopy compact features deep learning networks Neural nets Alzheimer's disease standard convolution mild cognitive impairment computer vision and image processing techniques Biomedical magnetic resonance imaging and spectroscopy convolutional neural nets depthwise convolution structural magnetic resonance images machine learning intelligent classification deep learning (artificial intelligence) image recognition classification tasks sequentially connected 3D mobile inverted bottleneck convolution block early diagnosis computer-aided diagnosis brain Patient diagnostic methods and instrumentation 3D MBConv block squeeze-and-excitation module medical image processing modified 3D EfficientNet

来源：评论

学校读者我要写书评

暂无评论

Maximum likelihood approach to image texture and acoustic signal classification

引用

IEE PROCEEDINGS-vision image AND SIGNAL processing 1999年第1期146卷 34-39页

作者： Thyagarajan, KS Nguyen, T Persons, CE San Diego State Univ Dept Elect & Comp Engn San Diego CA 92182 USA RDTE NCCOSC San Diego CA 92152 USA

The authors describe a method of classifying natural textures based on the maximum likelihood parameter estimation technique. The novelty of the technique lies in the use of textural features that are derived from the subbands of a wavelet transformed image via the co-occurrence matrices. A maximum likelihood classifier is designed using a set of training texture samples. Ten different Brodotz textures have been classified using this procedure with an average classification accuracy of 99.7%. The main emphasis is to apply this technique to the classification of underwater acoustic signals. A time-frequency plot is obtained for each segment of the acoustic signal and then converted to an intensity pattern. The textural classification scheme is then applied to the intensity patterns of the acoustic signals. Eight different underwater acoustic signals have been classified by this procedure with an average accuracy of 99.99%.

关键词： Sonar and acoustic radar image classification Acoustic signal processing Simulation, modelling and identification maximum likelihood estimation transform coding acoustic signal processing average accuracy time-frequency plot intensity patterns maximum likelihood parameter estimation co-occurrence matrices training texture samples image representation image resolution computer vision and image processing techniques Brodotz textures multiresolution representation acoustic signal classification image coding underwater sound average classification accuracy subbands Integral transforms in numerical analysis Underwater sound textural features image texture image and video coding wavelet transformed image underwater acoustic signals image texture classification wavelet transforms maximum likelihood classifier wavelet transform

来源：评论

学校读者我要写书评

暂无评论

An image layered scrambling encryption algorithm based on a novel discrete chaotic map

引用

IET image processing 2023年第2期17卷 518-532页

作者： Tang, Jianeng Zhang, Zezong Chen, Peiyang Zhang, Feng Ni, Hui Huang, Zhongming Huaqiao Univ Coll Engn Quanzhou Peoples R China Huaqiao Univ Coll Informat Sci & Engn Xiamen Peoples R China Fujian MM Elect Co Ltd Quanzhou Peoples R China

At present, the image encryption algorithm based on the bit-plane has the problem that the encryption speed and the encryption effect cannot be well balanced. To address the problem, an image layered scrambling encryption algorithm is proposed in this paper. First, a new one-dimensional Cosine Logistic compound chaotic map (1DCLC) is proposed. Several characteristics of the new chaotic map are analyzed by using various measures, such as bifurcation diagram, Lyapunov exponent, sample entropy etc. And the results show that the novel chaotic map has a better chaotic performance. Second, based on the chaotic map, an image encryption algorithm is proposed. The algorithm first performs an XOR encryption operation on the image. Second, the layered scrambling is applied to the XOR encrypted image. Then the layered and scrambled image is recombined for the second XOR encryption operation. In particular, in the layered scrambling, not only can the position of the pixel be changed but also the value of the pixel can be modified, which improves the security of the algorithm. In addition, in order to defend against various plaintext attacks and increase the security of the overall algorithm, the Hash function is introduced to update the key of the proposed algorithm. Finally, the original algorithm is improved and the improved algorithm's ability to resist differential attacks is analyzed. The experimental simulation and security test results show that the proposed encryption algorithm has a comparable encryption effect and a faster encryption speed.

关键词： XOR encryption operation improved algorithm Cryptography image layered scrambling novel chaotic map chaotic performance image encryption algorithm Optical, image and video signal processing faster encryption speed computer vision and image processing techniques chaos image processing XOR encrypted image Data security entropy one-dimensional Cosine Logistic compound chaotic map novel discrete chaotic map comparable encryption effect bifurcation cryptography layered scrambled image

来源：评论

学校读者我要写书评

暂无评论

Interpretation of colour maps - A combination of automatic and interactive techniques

引用

COMPUTING & CONTROL ENGINEERING JOURNAL 2001年第4期12卷 188-196页

作者： Ablameyko, S Bereishik, V Homenko, M Paramonova, N Patsko, O Belarussian Acad Sci Inst Engn Cybernet Minsk 220012 BELARUS

The article describes a system and technology for the automatic/interactive interpretation of colour maps. Due to the fact that a completely automatic solution is impossible, a combination of automatic and interactive techniques is used. Firstly, colour recognition and separation are performed. For automatic map vectorisation, a special fast scheme is used. To make digitisation more automatic and user friendly, an interactive digitising mode has been developed to extract line-based cartographic objects from vectorised data. The system is used successfully in the digitisation of topographic and other types of map.

关键词： map digitisation interactive digitising mode cartography image colour analysis colour map interpretation User interfaces special fast scheme automatic/interactive interpretation vectorised data image recognition Geography and cartography computing object recognition colour recognition computer vision and image processing techniques automatic map vectorisation interactive techniques interactive systems image recognition line-based cartographic objects

来源：评论

学校读者我要写书评

暂无评论

Spatial kernel K-harmonic means clustering for multi-spectral image segmentation

引用

IET image processing 2007年第2期1卷 156-167页

作者： Li, Q. Mitianoudis, N. Stathaki, T. Univ London Imperial Coll Sci Technol & Med Commun & Signal Proc Grp London SW7 2AZ England

The problem of image segmentation using intensity clustering approaches has been addressed in the literature. Grouping pixels of similar intensity to form clusters in an image have been tackled using a number of methods, such as the K-means (KM) algorithm. The K-harmonic means (KHM) was proposed to overcome the sensitivity of KM to centre initialisation. The use of a spatial kernel-based KHM (SKKHM) algorithm on the problem of image segmentation has been investigated. Instead of the original Euclidean intensity distance, a robust kernel-based KHM metric is employed to reduce the effect of outliers and noise. Spatial image information is also incorporated in the proposed clustering scheme, derived from Markov random field modelling. An extension of the proposed algorithm to multi-spectral imaging applications is also presented. Experimental results for both single-channel and multi-channel images demonstrate the robust performance of the proposed SKKHM algorithm.

关键词： spatial kernel K-harmonic means clustering image denoising Markov random field modelling computer vision and image processing techniques intensity clustering approach noise reduction multi-channel image Markov processes single-channel image spatial image information multi-spectral image segmentation Optical, image and video signal processing image segmentation

来源：评论

学校读者我要写书评

暂无评论

Graphical route information panel for the urban freeway network in Shanghai, China

引用

IET INTELLIGENT TRANSPORT SYSTEMS 2010年第3期4卷 212-220页

作者： Gan, H. Univ Shanghai Sci & Technol Sch Business Ctr Transport Res Shanghai Peoples R China

The concept of using graphical route information panel (GRIP) to improve the dynamic traffic management efficiency is becoming increasingly popular recently. Colour-coded level-of-service (LOS) map and route travel time are important information displayed by GRIP. This study addresses the graphical information provision issue and the travel time prediction issue, based on research and development of Shanghai urban freeway GRIPs. It first presents function and location of Shanghai GRIP, philosophy of GRIP panel layout and basic principle of LOS display method. Then it focuses on segmentation of LOS map and proposes three segmentation approaches: the detector-based approach, the ramp-based approach and the hybrid approach. Opinions and lessons learned regarding advantages and disadvantages of different segmentation approaches are given. Next, it proposes a macroscopic traffic flow model-based travel time prediction approach for GRIP. The traffic flow model incorporated in the prediction approach is a validated high-order continuum model. The preliminary performance test of the approach is conducted using real-traffic data of a three-lane urban freeway section of Yan-An elevated road in Shanghai. The results reveal that the travel time prediction approach performs well both under free-flowing conditions and under congested conditions. Last, it gives concluding remarks.

关键词： Traffic engineering computing continuum model colour coded level-of-service map traffic information systems ramp based map segmentation China traffic management urban freeway network automated highways computer vision and image processing techniques graphical route information panel detector based map segmentation road traffic macroscopic traffic flow model route travel time image segmentation Shanghai

来源：评论

学校读者我要写书评

暂无评论

image thresholding framework based on two-dimensional digital fractional integration and Legendre moments'

引用

IET image processing 2012年第6期6卷 717-727页

作者： Nakib, A. Schulze, Y. Petit, E. Univ Paris EST Creteil LISSI EA 3956 F-94010 Creteil France

In this study, the authors present a new image segmentation algorithm based on two-dimensional digital fractional integration (2D-DFI) that was inspired from the properties of the fractional integration function. Although obtaining a good segmentation result corresponds to finding the optimal 2D-DFI order, the authors propose a new alternative based on Legendre moments. This framework, called two dimensional digital fractional integration and Legendre moments' (2D-DFILM), allows one to include contextual information such as the global object shape and exploits the properties of the 2D fractional integration. The efficiency of 2D-DFILM is shown by the comparison to other six competing methods recently published and it was tested on real-world problem.

关键词： integration fractional integration function two dimensional digital fractional integration-Legendre moments image segmentation 2D fractional integration image segmentation algorithm computer vision and image processing techniques 2D-DFILM global object shape optimal 2D-DFI order Optical, image and video signal processing Mathematical analysis image thresholding framework

来源：评论

学校读者我要写书评

暂无评论

Marker-based quadri-ocular tracking system for surgery

引用

IET computer vision 2012年第5期6卷 435-441页

作者： He, Q. Wei, N. Li, B. Hu, C. Meng, M. Q. -H. Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Zhejiang Univ Ningbo Inst Technol Coll Informat Ningbo Zhejiang Peoples R China Chinese Univ Hong Kong Dept Elect Engn Hong Kong Hong Kong Peoples R China

This study presents a quadri-ocular tracking system, which is based on PC and infrared reflective markers, for a spine surgical robot. The authors mainly focus on four tasks of the system. First of all, a two-step strategy for point correspondence of the multi-ocular system is introduced. The strategy enhances the traditional epipolar constrain for a bi-ocular system, and it decomposes the point correspondence of the multi-ocular system into several bi-ocular systems and corresponding steps to improve the speed of the system. Second, this paper proposes a fast algorithm of three-dimensional point reconstruction based on the perpendicular feet of back-projection lines. A marker constraint is also dug up to solve the combination problem of target recognition. Finally, this study uses a generalised inverse and singular value decomposition-based method to locate the pose of the target. The experiments show that the speed and accuracy of the system are satisfactory.

关键词： Robotics infrared reflective markers Biology and medical computing image recognition Biological and medical control systems target recognition perpendicular feet Biophysics of neurophysiological processes biomedical optical imaging medical robotics three-dimensional point reconstruction epipolar constrain image reconstruction PC multi-ocular system singular value decomposition-based method generalised inverse method infrared imaging computer vision and image processing techniques medical image processing back-projection lines neurophysiology image recognition singular value decomposition Patient care and treatment spine surgical robot marker-based quadri-ocular tracking system bi-ocular system surgery

来源：评论

学校读者我要写书评

暂无评论

Salient region growing based on Gaussian pyramid

引用

IET image processing 2021年第13期15卷 3142-3152页

作者： Jiao, Jianjun Wang, Xiaopeng Zhang, Jungping Wang, Qingsheng Lanzhou Jiaotong Univ Sch Elect & Informat Engn Lanzhou 730070 Peoples R China

For region growing image segmentation, seed selection and image noise are two major concerns causing negative segmentation performance. This paper proposes a regional growth algorithm based on the Gaussian pyramid (GPRG), which automatically selects seed points and optimizes the growth path. To achieve automatic seed selection, Gaussian difference pyramid generated by the Gaussian pyramid is required. The growing seed of the salient target in an image is acquired by searching for extremums in each image of the Gaussian difference pyramid. For growing path optimization, edge changing direction is updated according to different Gaussian difference pyramid images with sizes from small to large. The edge of region growing is determined by the edge of the salient target in an image. Segmentation experiments show that this algorithm is able to automatically select seeds and accurately segment the salient target in an image with and without image noise. Performances in terms of segmentation accuracy (SA), mean intersection-over-union (mIoU) and E-measure are superior compared with other methods.

关键词： Optical, image and video signal processing computer vision and image processing techniques Other topics in statistics Other topics in statistics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：