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Conference on image processing - algorithms and systems xi

作者： Romanenko, I. V. Edirisinghe, E. A. Larkin, D. Univ Loughborough Dept Comp Sci Loughborough Leics England

ISBN: (纸本)9780819494283

image de-noising in the spatial-temporal domain has been a problem studied in-depth in the field of digital image processing. However complexity of algorithms often leads to high hardware resource usage, or computational complexity and memory bandwidth issues, making their practical use impossible. In our research we attempt to solve these issues with an optimized implementation of a practical spatial-temporal de-noising algorithm Spatial-temporal filtering was performed in Bayer RAW data space, which allowed us to benefit from predictable sensor noise characteristics and reduce memory bandwidth requirements. The proposed algorithm efficiently removes different kinds of noise in a wide range of signal to noise ratios. In our algorithm the local motion compensation is performed in Bayer RAW data space, while preserving the resolution and effectively improving the signal to noise ratios of moving objects. The main challenge for the use of spatial-temporal noise reduction algorithms in video applications is the compromise between the quality of the motion prediction and the complexity of the algorithm and required memory bandwidth In photo and video applications it is very important that moving objects should stay sharp, while the noise is efficiently removed in both the static background and moving objects. Another important use case is the case when background is also non-static as well as the foreground where objects are also moving. Taking into account the achievable improvement in PSNR (on the level of the best known noise reduction techniques, like VBM3D) and low algorithmic complexity, enabling its practical use in commercial video applications, the results of our research can be very valuable.

关键词： spatial-temporal de-noising image processing sensor noise Bayer RAW non-local means FPGA real-time motion compensation

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Visual quality analysis for images degraded by different types of noise

Visual quality analysis for images degraded by different typ...

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Conference on image processing - algorithms and systems xi

作者： Ponomarenko, Nikolay N. Lukin, Vladimir V. Ieremeiev, Oleg I. Egiazarian, Karen O. Astola, Jaakko T. Natl Aerosp Univ UA-61070 Kharkov Ukraine

ISBN: (纸本)9780819494283

Modern visual quality metrics take into account different peculiarities of the Human Visual System (HVS). One of them is described by the Weber-Fechner law and deals with the different sensitivity to distortions in image fragments with different local mean values (intensity, brightness). We analyze how this property can be incorporated into a metric PSNR-HVS-M. It is shown that some improvement of its performance can be provided. Then, visual quality of color images corrupted by three types of i.i.d. noise (pure additive, pure multiplicative, and signal dependent, Poisson) is analyzed. Experiments with a group of observers are carried out for distorted color images created on the basis of TID2008 database. Several modern HVS-metrics are considered. It is shown that even the best metrics are unable to assess visual quality of distorted images adequately enough. The reasons for this deal with the observer's attention to certain objects in the test images, i.e., with semantic aspects of vision, which are worth taking into account in design of HVS-metrics.

关键词： full-reference quality assessment human vision system image analysis noisy color images

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Using Planar Embedded DRAM in Memory Intensive Signal processing Circuits: Case Studies on LDPC Decoding and Motion Estimation

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JOURNAL OF SIGNAL processing systems FOR SIGNAL image AND VIDEO TECHNOLOGY 2013年第1期73卷 11-24页

作者： Venkataraman, Kalyana Sundaram Li, Yiran Wu, Qi xie, Ningde Sun, Hongbin Zheng, Nanning Zhang, Tong Rensselaer Polytech Inst Dept Elect Comp & Syst Engn Troy NY 12180 USA Xi An Jiao Tong Univ Xian 710049 Shaanxi Peoples R China

This paper studies the feasibility and potential of using planar embedded DRAM (eDRAM), which is completely compatible with CMOS logic process, to improve circuit implementation efficiency of memory-hungry signal processing algorithms. In spite of its apparent cell area efficiency advantage over SRAM, planar eDRAM is not being widely used in practice, mainly due to its very short retention time (e.g., few s and even a few hundreds ns). In this work, we contend that short retention time may not necessarily be a fundamental issue for implementing signal processing algorithms because they typically handle streaming data, which exhibits regular and predictable data access patterns, and has a large algorithm/architecture design space. This study elaborates on the rationale and application of using a planar eDRAM in memory-hungry signal processing circuit implementations, and discusses the possible algorithm and architecture design strategies to better embrace the use of planar eDRAM. For the purpose of demonstration, we use low-density parity-check (LDPC) code decoding and motion estimation in video encoding as test vehicles. Beyond a straightforward SRAM replacement, we propose an interleaved read/write page-mode DRAM operation to reduce planar eDRAM energy consumption by leveraging LDPC code decoding data access pattern, and we investigate the potential of using planar eDRAM to enable a higher degree of image data reuse in motion estimation by proposing a folded scan structure to further improve its effectiveness. We carried out detailed planar eDRAM SPICE simulations at 45 nm node to obtain its characteristics, based on which we quantitatively evaluate the effectiveness of using planar eDRAM in these two case studies.

关键词： Planar eDRAM Signal processing LDPC decoder Motion estimation

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A real-time ellipse detection method using GPU-based RANSAC

A real-time ellipse detection method using GPU-based RANSAC

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2013 5th International Conference on Intelligent Human-Machine systems and Cybernetics, IHMSC 2013

作者： Liu, Liu Yang, Jianfeng University of Chinese Academy of Sciences Beijing China Key laboratory of spectrum imaging technology Xi'an Institute of Optics and Fine Mechanics CAS Xi'an China Xi'an Institute of Optics and Fine Mechanics Chinese Academy of Sciences Xi'an China

ISBN: (纸本)9780769550114

An approach to very rapid and real-time ellipse detection is described, Based on a modified RANSAC (RANdom Sample Consensus), and considering the parallel processing capabilities of a programmable graphics processing unit. The method is able to detect ellipses of images in real-time. First, it finished the computational part of image segmentation and contour detection on the CPU. Then it uses the fragment processing capability of the GPU to fit ellipse shape parameters. Experimental results show that the computational efficiency of the proposed method will be multiplied several times than other algorithms, and this method is more efficient for real-time ellipse detection. © 2013 IEEE.

关键词： Graphics processing unit

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Brain MR image Segmentation Based on an Adaptive Combination of Global and Local Fuzzy Energy

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MATHEMATICAL PROBLEMS IN ENGINEERING 2013年第1期2013卷 1-10页

作者： Cui, Wenchao Wang, Yi Lei, Tao Fan, Yangyu Feng, Yan Northwestern Polytech Univ Sch Elect & Informat Xian 710072 Peoples R China China Three Gorges Univ Coll Sci Yichang 443002 Peoples R China Lanzhou Jiaotong Univ Sch Elect & Informat Engn Lanzhou 730070 Peoples R China

This paper presents a novel fuzzy algorithm for segmentation of brain MR images and simultaneous estimation of intensity inhomogeneity. The proposed algorithm defines an objective function including a local fuzzy energy and a global fuzzy energy. Based on the assumption that the local image intensities belonging to each different tissue satisfy Gaussian distributions with different means, we derive the local fuzzy energy by utilizing maximum a posterior probability (MAP) and Bayes rule. The global fuzzy energy is defined by measuring the distance between the original image and the corresponding inhomogeneity-free image. We combine the global fuzzy energy with the local fuzzy energy using an adaptive weight function whose value varies with the local contrast of the image. This combination enables the proposed algorithm to address intensity inhomogeneity and to improve the accuracy of segmentation and its robustness to initialization. Besides, the proposed algorithm incorporates neighborhood spatial information into the membership function to reduce the impact of noise. Experimental results for synthetic and real images validate the desirable performances of the proposed algorithm.

关键词： BRAIN imaging MAGNETIC resonance imaging of the brain SEGMENTATION (image processing) ADAPTIVE computing systems FUZZY algorithms GAUSSIAN distribution

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Wireless Multimedia Sensor Networks on Reconfigurable Hardware: Information Reduction Techniques 1

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2013年

作者： Li-minn Ang, Kah Phooi Seng, Li Wern Chew, Lee Seng Yeong, Wai Chong Chia (auth.)

ISBN: (数字)9783642382031

ISBN: (纸本)9783642382024;9783642382031

Traditional wireless sensor networks (WSNs) capture scalar data such as temperature, vibration, pressure, or humidity. Motivated by the success of WSNs and also with the emergence of new technology in the form of low-cost image sensors, researchers have proposed combining image and audio sensors with WSNs to form wireless multimedia sensor networks (WMSNs). This introduces practical and research challenges, because multimedia sensors, particularly image sensors, generate huge amounts of data to be processed and distributed within the network, while sensor nodes have restricted battery power and hardware resources. This book describes how reconfigurable hardware technologies such as field-programmable gate arrays (FPGAs) offer cost-effective, flexible platforms for implementing WMSNs, with a main focus on developing efficient algorithms and architectures for information reduction, including event detection, event compression, and multicamera processing for hardware implementations. The authors include a comprehensive review of wireless multimedia sensor networks, a complete specification of a very low-complexity, low-memory FPGA WMSN node processor, and several case studies that illustrate information reduction algorithms for visual event compression, detection, and fusion. The book will be of interest to academic researchers, R&D engineers, and computer science and engineering graduate students engaged with signal and video processing, computer vision, embedded systems, and sensor networks.

关键词： Computer engineering. Computer network architectures. Computer vision. Multimedia systems. Wireless sensor networks

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An image-based approach for automatic detecting five true-leaves stage of cotton

An image-based approach for automatic detecting five true-le...

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8th Symposium on Multispectral image processing and Pattern Recognition (MIPPR) - Remote Sensing image processing, Geographic Information systems, and Other Applications

作者： Li, Yanan Cao, Zhiguo Wu, xi Yu, Zhenghong Wang, Yu Bai, xiaodong Natl Key Lab Sci & Tech Multispectral Informat Pr Wuhan 430074 Peoples R China

ISBN: (纸本)9780819498069

Cotton, as one of the four major economic crops, is of great significance to the development of the national economy. Monitoring cotton growth status by automatic image-based detection makes sense due to its low-cost, low-labor and the capability of continuous observations. However, little research has been done to improve close observation of different growth stages of field crops using digital cameras. Therefore, algorithms proposed by us were developed to detect the growth information and predict the starting date of cotton automatically. In this paper, we introduce an approach for automatic detecting five true-leaves stage, which is a critical growth stage of cotton. On account of the drawbacks caused by illumination and the complex background, we cannot use the global coverage as the unique standard of judgment. Consequently, we propose a new method to determine the five true-leaves stage through detecting the node number between the main stem and the side stems, based on the agricultural meteorological observation specification. The error of the results between the predicted starting date with the proposed algorithm and artificial observations is restricted to no more than one day.

关键词： automatic image-based detection five true-leaf stage computer vision color segmentation Mean shift Hough transformation chain code

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Design and implementation for image reconstruction of CompressiveSensing using FPGA

Design and implementation for image reconstruction of Compre...

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3rd Annual IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent systems, IEEE-CYBER 2013

作者： Bi, Sheng xi, Ning Lai, King Wai Chiu Pan, Xuwei Department of Mechanical and Biomedical Engineering City University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9781479906109

A novel single pixel camera system has been introduced to overcome the current limitation and challenges of traditional focal plane arrays. This new hardware system mainly employs one photo-sensing element/pixel and a digital micromirror device (DMD). By consideration of a new mathematical theory and algorithms of compressive sampling, we can reconstruct images based on the measurement results of the photo-sensing element. However, the development reminds challenge. Since large amount of data is accessed and the inherent delay of instruction cycle within transporting data on the DMD, it makes real-time processing of image recovery difficult. Conventionally, the pattern data was transported to DMD from PC through USB interface. Since the USB interface limited the data transfer speed, the total time of signal collection and image reconstruction was about 30 minutes. In this paper, FPGA is used to transport data from SDRAM to control the DMD, and at the same time, the signal of the photo-sensing element is acquired. As a result the control of the DMD can be improved and imaging processing time can be reduced. The development includes various components such as SDRAM interface, FIFO Data buffer, ADC interface, USB interface and DMD control interface. Comparing with the method of transporting data through PC, the time for image recovery is greatly reduced. © 2013 IEEE.

关键词： Compressed sensing

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Benchmarking asymmetric 3D-2D face recognition systems

Benchmarking asymmetric 3D-2D face recognition systems

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2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2013

作者： Zhao, xi Zhang, Wuming Evangelopoulos, Georgios Huang, Di Shah, Shishir K. Wang, Yunhong Kakadiaris, Ioannis A. Chen, Liming Computational Biomedicine Lab Department of Computer Science University of Houston Houston TX 77204-3010 United States LIRIS Lab Ecole Centrale de Lyon 69134 cedex France Laboratory of Intelligent Recognition and Image Processing School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781467355452

Asymmetric 3D-2D face recognition (FR) aims to recognize individuals from 2D face images using textured 3D face models in the gallery (or vice versa). This new FR scenario has the potential to be readily deployable in field applications while still keeping the advantages of 3D FR solutions of being more robust to pose and lighting variations. In this paper, we propose a new experimental protocol based on the UHDB11 dataset for benchmarking 3D-2D FR algorithms. This new experimental protocol allows for the study of the performance of a 3D-2D FR solution under pose and/or lighting variations. Furthermore, we also benchmarked two state of the art 3D-2D FR algorithms. One is based on the Annotated Deformable Model (using manually labeled landmarks in this paper) using manually labeled landmarks whereas the other makes use of Oriented Gradient Maps along with an automatic pose estimation through random forest. © 2013 IEEE.

关键词： Face recognition

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Featured circular profile for vessel thresholding

Featured circular profile for vessel thresholding

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Congress on image and Signal processing, CISP

作者： Na Lu Hongyu Miao State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an Shaanxi China Department of Biostatistics and Computational Biology University of Rochester NY USA

ISBN: (纸本)9781479927654

To analyze the characteristics of the blood vessels quantitatively is of great importance to the diagnosis of different diseases, e.g., stenosis, diabetic retinopathy, tumor and so on. However, the occurrence of imaging noise or illumination variation may include difficulty for image analysis, especially for accurate quantitative analysis. Therefore, more efficient algorithms for vessel image thresholding, segmentation or extraction have been studied. Nevertheless, these methods may still fail entirely in case of images with large noise or structural noise (such as spots that obscure and/or are brighter than vessels). To improve the algorithm performance on these issues, we propose a novel thresholding algorithm for vascular images by probing the polarity in the circular profiles (PCP) of image pixels. This can robustly distinguish tube-like objects from both cloud-like contaminations and structural noise. Extensive simulation studies based on multiple evaluation criteria suggest that the PCP algorithm typically has a superior performance over other representative approaches. Finally, we also demonstrate the satisfactory performance of the PCP method on real image data.

关键词： Noise Contamination Probes Algorithm design and analysis Shape Signal processing algorithms Graphical models

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