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Nonlocal Joint Regularizations Framework with Application to image Denoising

CIRCUITS systems AND SIGNAL processing 2016年第8期35卷 2932-2942页

作者： Li, Ao Chen, Deyun Lin, Kezheng Sun, Guanglu Harbin Univ Sci & Technol Postdoctoral Res Stn Sch Comp Sci & Technol XueFu Rd 52 Harbin 150080 Peoples R China

Low-rank (LR) representation and the nonlocal model (NLM) are important techniques in the field of image restoration, offering significant improvements over many current recovery algorithms. Natural images contain global and local redundancy, and this can be utilized to enhance the restoration performance. Thus, we propose a novel optimization framework that incorporates the benefits of LR and NLM. First, NLM is employed to search for similar patches to reduce the global redundancy. An LR model is then exploited as the prior knowledge needed to constrain the low-rank property of the searched patches. We also use a 3D sparse model to constrain the local sparsity of these patches, thus preserving their underlying structure more effectively. To solve the minimization problem within our novel framework, we describe an iterative scenario that uses an alternating optimization method based on the improved split Bregman technique. Experimental results demonstrate that our proposed method outperforms several state-of-the-art algorithms.

关键词： image restoration Low rank Nonlocal model 3D Sparsity Split Bregman

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A Novel image Encryption Algorithm Based on Multiple Chaotic systems and Self-adaptive Model 1

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4th International Conference on Communications, Signal processing, and systems (CSPS)

作者： Wang, Chengqi Zhang, Xiao Zheng, Zhiming Beihang Univ Minist Educ Key Lab Math Informat & Behav Semant Beijing 100191 Peoples R China Beihang Univ Sch Math & Syst Sci Beijing 100191 Peoples R China

ISBN: (数字)9783662498316

ISBN: (纸本)9783662498316;9783662498293

In recent years, image encryption has attracted much attention. Particularly, due to large data capacity and high correlation among pixels, chaos-based image encryption algorithms are more suitable to be applied in the digital image encryption. In this paper, we propose a novel chaotic image encryption algorithm, in which novel multiple chaotic systems and efficient self-adaptive model are initially mingled to enhance the security. Different from conventional algorithms, plaintext participates in the generation of cryptograph in a new way, which follows the idea from the perceptron model. The proposed algorithm enlarges the key space, enhances the randomness of the algorithm, and resists the differential attack effectively. Simulation results are demonstrated that proposed algorithm possesses the high security for the main current attacks, which is an excellent candidate for practical applications of image encryption.

关键词： image encryption Multiple chaotic systems Self-adaptive model Perceptron model

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Visual Informatics Tools for Supporting Large-Scale Collaborative Wildlife Monitoring with Citizen Scientists

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IEEE CIRCUITS AND systems MAGAZINE 2016年第1期16卷 73-86页

作者： He, Zhihai Kays, Roland Zhang, Zhi Ning, Guanghan Huang, Chen Han, Tony X. Millspaugh, Josh Forrester, Tavis McShea, William Univ Missouri Dept Elect & Comp Engn Columbia MO 65211 USA N Carolina State Univ Raleigh NC 27695 USA NC Museum Nat Sci Biodivers Lab Raleigh NC USA Univ Missouri Columbia MO 65211 USA Univ Missouri Elect & Comp Engn Columbia MO 65211 USA Univ Missouri Sch Nat Resources Wildlife Management Columbia MO 65211 USA Univ Missouri Sch Nat Resources Columbia MO 65211 USA Smithsonian Inst Washington DC 20560 USA

Collaborative wildlife monitoring and tracking at large scales will help us understand the complex dynamics of wildlife systems, evaluate the impact of human actions and environmental changes on wildlife species, and answer many important ecological and evolutionary research questions. To support collaborative wildlife monitoring and research, we need to develop integrated camera-sensor networking systems, deploy them at large scales, and develop advanced computational and informatics tools to analyze and manage the massive wildlife monitoring data. In this paper, we will cover various aspects of the design of such systems, including (1) long-lived integrated camera-sensor system design, (2) image processing and computer vision algorithms for animal detection, segmentation, tracking, species classification, and biometric feature extraction, (3) cloud-based data management, (4) crowd-sourcing based image annotation with citizen scientists, and (5) applications to wildlife and ecological research.

关键词： Wildlife Monitoring Collaboration Feature extraction Visualization Informatics Computer vision System analysis and design image processing Biometrics

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image scanning techniques for speeded-up color object detection 5th

Image scanning techniques for speeded-up color object detect...

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5th Eccomas Thematic Conference on Computational Vision and Medical image processing, Vipimage 2015

作者： Trifan, Alina Neves, António J. R. Cunha, Bernardo Department of Electronics and Telecommunications Engineering Intelligent Systems and Intelligent Robotics Laboratory Institute of Electronics and Informatics Engineering of Aveiro University of Aveiro Portugal

ISBN: (纸本)9781138029262

Nowadays there are many computer vision algorithms dedicated to solve the problem of object detection, from many different perspectives. Many of these algorithms take a considerable processing time even for low resolution images. Research areas that are more concerned about real-time capabilities of a system, such as the case of robotics for example, are focusing on adapting the existing algorithms or developing new ones that cope with time constraints. Color object detection algorithms are often used in time-constrained application since the color of an object is an important clue for its detection. In addition, color segmentation algorithms have a smaller computational cost than generic object detection algorithms. Most of the color object detection algorithms include a step of image scanning in search of pixels of the color of interest. In this paper we present a study on the influence of an image scanning pattern while searching for pixels of a certain color versus the image resolution in the results of three color object detection algorithms. We present results comparing different scanning approaches versus different resolution images for color object detection algorithms based on blob formation, contours detection and region growing clustering. Our experiments show that using search lines for color segmentation, followed by blob formation provides faster and more accurate results. © 2016 Taylor & Francis Group, London.

关键词： Color

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Approximate subgraph isomorphism for image localization 14

Approximate subgraph isomorphism for image localization

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image processing: algorithms and systems xiv 2016

作者： Shankar, Vaishaal Zhang, Jordan Chen, Jerry Dinh, Christopher Clements, Mattthew Zakhor, Avideh University of California Berkeley BerkeleyCA94720 United States

We propose a system for user-aided image localization in urban regions by exploiting the inherent graph like structure of urban streets, buildings and intersections. In this graph the nodes represent buildings, intersections and roads. The edges represent "logical links" such as two buildings being next to each other, or a building being on a road. We generate this graph automatically for large areas using publicly available road and building footprint data. To localize a query image, a user generates a similar graph manually by identifying the buildings, intersections and roads in the image. We then run a subgraph isomorphism algorithm to find candidate locations for the the query image. We evaluate our system on regions of multiple sizes ranging from 2km2 to 47km2 in the Amman,Jordan and Berkeley,CA,USA. We have found that in many cases we reduce the uncertainty in the query’s location by as much as 90 percent. © 2016 Society for Imaging Science and Technology.

关键词： Buildings

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QUANTITATIVE STUDY OF image FEATURES OF CLUSTERED MICROCALCIFICATIONS IN FOR-PRESENTATION MAMMOGRAMS 23

QUANTITATIVE STUDY OF IMAGE FEATURES OF CLUSTERED MICROCALCI...

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23rd IEEE International Conference on image processing (ICIP)

作者： Wang, Juan Yang, Yongyi Nishikawa, Robert M. Illinois Inst Technol Dept Elect & Comp Engn Chicago IL 60616 USA Univ Pittsburgh Dept Radiol Pittsburgh PA 15213 USA

ISBN: (纸本)9781467399616

Mammogram images are now increasingly acquired with full-field digital mammography (FFDM) systems in the clinics. Traditionally, the "for-processing" format of FFDM images is used in computer-aided diagnosis (CAD) of breast cancer. In this study, we investigate the feasibility of using "for-presentation" format of FFDM (which are more readily available) in development of CAD algorithms for microcalcification (MC) lesions. We conduct a quantitative evaluation of both the image features and the detectability of individual MCs on a set of 188 mammograms acquired in both formats. The results demonstrate that there is a high degree of agreement in the image features between the two image formats, and that a slight increase in false-positives in MC detection is observed in for-presentation images.

关键词： Computer-aided diagnosis (CAD) full-field digital mammography (FFDM) microcalcifications

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Applying image Features and AdaBoost Classification for Vehicle Detection in the 'SM4Public' System

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8th International Conference on image processing and Communications (IP and C)

作者： Frejlichowski, Dariusz Gosciewska, Katarzyna Forczmanski, Pawel Nowosielski, Adam Hofman, Radoslaw West Pomeranian Univ Technol Fac Comp Sci Zolnierska 52 PL-71210 Szczecin Poland Smart Monitor Sp Zoo Niemierzynska 17a PL-71441 Szczecin Poland

ISBN: (纸本)9783319238142;9783319238135

The main goal of works described in the paper is to test and select algorithms to be implemented in the 'SM4Public' security system for public spaces. The paper describes the use of cascading approaches in the scenario concerning the detection of vehicles in static images. Three feature extractors were used along with benchmark datasets in order to prepare eight various cascades of classifiers. The algorithms selected for feature extraction are Histogram of Oriented Gradients, Local Binary Patterns and Haar-like features. AdaBoost was used as a classifier. The paper briefly introduces the 'SM4Public' system characteristics, characterizes the employed algorithms and presents sample experimental results.

关键词： Video surveillance Vehicle detection Cascades of classifiers

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A new framework for remote sensing image super-resolution: Sparse representation-based method by processing dictionaries with multi-type features

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JOURNAL OF systems ARCHITECTURE 2016年 64卷 63-75页

作者： Wu, Wei Yang, Xiaomin Liu, Kai Liu, Yiguang Yan, Binyu Hua, Hua Sichuan Univ Coll Elect & Informat Engn Chengdu 610064 Sichuan Peoples R China Sichuan Univ Sch Elect Engn & Informat Chengdu 610064 Sichuan Peoples R China

Remote sensing images play an important role in many practical applications, however, due to the physical limitations of remote sensing devices, it is difficult to obtain images at an expecting high resolution level. Acquiring high-resolution(HR) images from the original low-resolution(LR) ones with super-resolution(SR) methods has always been an attractive proposition in embedded systems including various kinds of tablet PC and smart phone. SR methods based on sparse representation have been successfully used in processing remote sensing images, however, they have two major problems in common. First, they use only one type of image features to represent the low resolution(LR) images. However, one single type of features cannot accurately represent an image due to the diverse structures of the image, as a result, artifacts would be produced simultaneously. Second, many dictionary learning methods try to build a universal dictionary with only one single type of features. However, apparently, a dictionary with a single type of features is not enough to capture the different structures of a remote sensing image, without any doubt, the resultant image would turn out to be a poor one. To overcome the problems above, we propose a new framework for remote sensing image super resolution: sparse representation-based SR method by processing dictionaries with multi-type features. First, in order to represent the remote sensing image more accurately, different types of features are extracted from images. Second, to achieve a better performance, various dictionaries with multi-type features are learned to capture the essential structures of the image. Then, it's proposed to adaptively control the weights of the high resolution(HR) patches obtained by different dictionaries. Numerous experiments validate that this proposed framework brings better results in terms of both objective quantitation and visual perception than other compared algorithms. (C) 2015 Elsevier B.V. All rights

关键词： Super-resolution Remote sensing images Dictionary interpreting Sparse representation

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Real-time Multi-camera Video Acquisition and processing Platform for ADAS

Real-time Multi-camera Video Acquisition and Processing Plat...

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Conference on Real-Time image and Video processing

作者： Saponara, Sergio Univ Pisa Dept Informat Engn Via G Caruso 16 I-56122 Pisa Italy

ISBN: (纸本)9781510601420

The paper presents the design of a real-time and low-cost embedded system for image acquisition and processing in Advanced Driver Assisted systems (ADAS). The system adopts a multi-camera architecture to provide a panoramic view of the objects surrounding the vehicle. Fish-eye lenses are used to achieve a large Field of View (FOV). Since they introduce radial distortion of the images projected on the sensors, a real-time algorithm for their correction is also implemented in a pre-processor. An FPGA-based hardware implementation, re-using IP macrocells for several ADAS algorithms, allows for real-time processing of input streams from VGA automotive CMOS cameras.

关键词： Real-time Video/image processing ADAS (Advanced Driving Assistance System) DSP (Digital Signal Processor) Traffic signs recognition Automotive electronics FPGA (Field Programmable Gate Array) CMOS camera

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Automated processing of Cytological and Histological images 12

Automated Processing of Cytological and Histological Images

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12th International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)

作者： Berezsky, Oleh Pitsun, Oleh Ternopil Natl Econ Univ CIT Dept Lvivska St 11 Ternopol Ukraine

The paper analyzes well-known automated microscopy systems. The work presents the comparative analysis of low-and middle-designed algorithms. The adaptive module of pre-processing and image segmentation has been worke... 详细信息

ISBN: (纸本)9786176079132

关键词： automated microscopy system algorithm image preprocessing and segmentation

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