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Conference on Airborne Intelligence, Surveillance, Reconnaissance (ISR) systems and Applications xi

作者： Paolini, Aaron Humphrey, John Curt, Petersen Kelmelis, Eric EM Photon 51 E Main StSte 203 Newark DE 19711 USA

ISBN: (纸本)9781628410136

Imaging scenarios commonly involve erratic, unpredictable camera behavior or subjects that are prone to movement, complicating multi-frame image processing techniques. To address these issues, we developed three techniques that can be applied to multi-frame image processing algorithms in order to mitigate the adverse effects observed when cameras are panning or subjects within the scene are moving. We provide a detailed overview of the techniques and discuss the applicability of each to various movement types. In addition to this, we evaluated algorithm efficacy with demonstrated benefits using field test video, which has been processed using our commercially available surveillance product. Our results show that algorithm efficacy is significantly improved in common scenarios, expanding our software's operational scope. Our methods introduce little computational burden, enabling their use in real-time and low-power solutions, and are appropriate for long observation periods. Our test cases focus on imaging through turbulence, a common use case for multi-frame techniques.

关键词： Turbulence Mitigation Long-Range Imaging Speckle Imaging Surveillance image processing image Enhancement Moving Targets ATCOM

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An Efficient Strategy for Bit-Quad-Based Euler Number Computing Algorithm

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IEICE TRANSACTIONS ON INFORMATION AND systems 2014年第5期E97D卷 1374-1378页

作者： Yao, Bin Wu, Hua Yang, Yun Chao, Yuyan Ohta, Atsushi Kawanaka, Haruki He, Lifeng Shaanxi Univ Sci & Technol Artificial Intelligence Inst Coll Elect & Informat Engn Xian 710021 Shaanxi Peoples R China Nagoya Sangyo Univ Grad Sch Environm Management Owariasahi 4888711 Japan Aichi Prefectural Univ Grad Sch Informat Sci & Technol Nagakute Aichi 4801198 Japan

The Euler number of a binary image is an important topological property for pattern recognition, and can be calculated by counting certain bit-quads in the image. This paper proposes an efficient strategy for improving the bit-quad-based Euler number computing algorithm. By use of the information obtained when processing the previous bit quad, the number of times that pixels must be checked in processing a bit quad decreases from 4 to 2. Experiments demonstrate that an algorithm with our strategy significantly outperforms conventional Euler number computing algorithms.

关键词： Euler number topological property computer vision pattern recognition binary image

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Evaluation of super-resolution imager with binary fractal test target 11

Evaluation of super-resolution imager with binary fractal te...

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Conference on Electro-Optical and Infrared systems - Technology and Applications xi

作者： Landeau, Stephane Direct Gen Armement F-92221 Bagneux France

ISBN: (纸本)9781628413120

Today, new generation of powerful non-linear image processing are used for real time super-resolution or noise reduction. Optronic imagers with such features are becoming difficult to assess, because spatial resolution and sensitivity are now related to scene content. Many algorithms include regularization process, which usually reduces image complexity to enhance spread edges or contours. Small important scene details can be then deleted by this kind of processing. In this paper, a binary fractal test target is presented, with a structured clutter pattern and an interesting autosimilarity multi-scale property. The apparent structured clutter of this test target gives a trade-off between a white noise, unlikely in real scenes, and very structured targets like MTF targets. Together with the fractal design of the target, an assessment method has been developed to evaluate automatically the non-linear effects on the acquired and processed image of the imager. The calculated figure of merit is to be directly comparable to the linear Fourier MTF. For this purpose the Haar wavelet elements distributed spatially and at different scales on the target are assimilated to the sine Fourier cycles at different frequencies. The probability of correct resolution indicates the ability to read correct Haar contrast among all Haar wavelet elements with a position constraint. For the method validation, a simulation of two different imager types has been done, a well-sampled linear system and an under-sampled one, coupled with super-resolution or noise reduction algorithms. The influence of the target contrast on the figures of merit is analyzed. Finally, the possible introduction of this new figure of merit in existing analytical range performance models, such as TRM4 (Fraunhofer IOSB) or NVIPM (NVESD) is discussed. Benefits and limitations of the method are also compared to the TOD (TNO) evaluation method.

关键词： image processing test target MTF target acquisition electro optical performance modeling

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Quantification of image registration error

Quantification of image registration error

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Conference on Polarization - Measurement, Analysis, and Remote Sensing xi

作者： Mahamat, Adoum H. Shields, Eric A. Sandia Natl Labs Albuquerque NM 87185 USA

ISBN: (纸本)9781628410365

image registration is a digital image processing technique that takes two or more of images of a scene in different-coordinate systems and transforms them into a single coordinate system. image registration is a necessary step in many advanced image processing techniques, such as multi-frame super-resolution. For that reason, registration accuracy is very crucial. While image registration is usually performed on images, one can perform the registration using metric images as well. This paper will present registration methods and their accuracies for various noise levels for the case of pure translational image motion. Registration techniques will be applied to the images themselves as well as to phase congruency images, gradient images, and edge-detected images. This study will also investigate registration of under-sampled images. Noise-free images are degraded using three types of noise: additive Gaussian noise, fixed-pattern noise along the column direction, and a combination of these two. The registration error is quantified for two registration algorithms with three different images as a function of the signal-to-noise ratio. A test on the usefulness of the image registration and registration accuracy performed on the intensity images of the Stokes imaging polarimeter. The Stokes images calculated before and after registration of the intensity images are compared to each other to show the improvement.

关键词： Super-resolution image registration metric registration Stokes polarimetric

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Robust real-time horizon detection in full-motion video

Robust real-time horizon detection in full-motion video

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Conference on Airborne Intelligence, Surveillance, Reconnaissance (ISR) systems and Applications xi

作者： Young, Grace B. Bagnall, Bryan Lane, Corey Parameswaran, Shibin La Jolla High Sch 750 Nautilus St La Jolla CA 92037 USA Space & Naval Warfare Syst Ctr Pacif San Diego CA 92152 USA

ISBN: (纸本)9781628410136

The ability to detect the horizon on a real-time basis in full-motion video is an important capability to aid and facilitate real-time processing of full-motion videos for the purposes such as object detection, recognition and other video/image segmentation applications. In this paper, we propose a method for real-time horizon detection that is designed to be used as a front-end processing unit for a real-time marine object detection system that carries out object detection and tracking on full-motion videos captured by ship/harbor-mounted cameras, Unmanned Aerial Vehicles (UAVs) or any other method of surveillance for Maritime Domain Awareness (MDA). Unlike existing horizon detection work, we cannot assume a priori the angle or nature (for e.g. straight line) of the horizon, due to the nature of the application domain and the data. Therefore, the proposed real-time algorithm is designed to identify the horizon at any angle and irrespective of objects appearing close to and/or occluding the horizon line (for e.g. trees, vehicles at a distance) by accounting for its non-linear nature. We use a simple two-stage hierarchical methodology, leveraging color-based features, to quickly isolate the region of the image containing the horizon and then perform a more fine-grained horizon detection operation. In this paper, we present our real-time horizon detection results using our algorithm on real-world full-motion video data from a variety of surveillance sensors like UAVs and ship mounted cameras confirming the real-time applicability of this method and its ability to detect horizon with no a priori assumptions.

关键词： Video Video surveillance Video processing Cameras Detection and tracking algorithms Unmanned aerial vehicles Feature extraction Sensors Surveillance Imaging systems

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Face hallucination based on locally linear embedding and local correlation 14

Face hallucination based on locally linear embedding and loc...

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2014 Conference on Research in Adaptive and Convergent systems, RACS 2014

作者： Nguyen, Vinh Hung, Chih-Cheng Ma, xiang Center for Biometrics Research Southern Polytechnic State University MariettaGA30060 United States Sino-US Intelligent Information Processing Lab. Anyang Normal University China School of Information Engineering Chang'an University Xi'an710061 China

ISBN: (纸本)9781450330602

In this paper, we propose a new face hallucination algorithm based on Locally Linear Embedding and Local Correlation method (LC-LLE). The LC-LLE algorithm is an improved locally linear embedding (LLE) algorithm by combining LLE algorithm and local correlation coefficients. The main difference between LC-LLE and LLE algorithms is that LC-LLE uses two different measures for searching the nearest neighbors for matching the most similar patches, while LLE uses only Euclidean distance for searching the nearest neighbors. Specifically, we calculate the Euclidean distance between the low-resolution input patch and patches in the low-resolution training images to select z-NN (i.e. z number of nearest patches). Then, we use the inner product for local correlation computation between the input patch and selected z-NN to identify k nearest neighbors (i.e. k-NN). After that the reconstruction weights are derived using k-NN patches, and generate the high-resolution image patches based on the reconstruction weights. Finally, high-resolution patches are synthesized into the high-resolution image. Experimental results show that the proposed method achieves better performance for high-resolution image reconstruction than Ma's LLE and PCA methods. © 2014 ACM.

关键词： Nearest neighbor search

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image SUPER-RESOLUTION USING MULTI-LAYER SUPPORT VECTOR REGRESSION

IMAGE SUPER-RESOLUTION USING MULTI-LAYER SUPPORT VECTOR REGR...

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IEEE International Conference on Acoustics, Speech and Signal processing

作者： Jie Xu Cheng Deng xinbo Gao Dacheng Tao Xuelong Li School of Electronic Engineering Xidian University Xi'an 710071 China Centre for Quantum Computation & Intelligent Systems University of Technology Sydney Australia Xi'an Institute of Optics and Precision Mechanics CAS Xi'an 710119 China

ISBN: (纸本)9781479928941

Existing support vector regression (SVR) based image super-resolution (SR) methods always utilize single layer SVR model to reconstruct source image, which are incapable of restoring the details and reduce the reconstruction quality. In this paper, we present a novel image SR approach, where a multi-layer SVR model is adopted to describe the relationship between the low resolution (LR) image patches and the corresponding high resolution (HR) ones. Besides, considering the diverse content in the image, we introduce pixel-wise classification to divide pixels into different classes, such as horizontal edges, vertical edges and smooth areas, which is more conductive to highlight the local characteristics of the image. Moreover, the input elements to each SVR model are weighted respectively according to their corresponding output pixel's space positions in the HR image. Experimental results show that, compared with several other learning-based SR algorithms, our method gains high-quality performance.

关键词： images imagery (Psychotherapy) source image image pixel Quality factor multilayers SAVANNAH RIVER OPERATIONS OFFICE Strontium

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image Segmentation Using FCM Optimized by Quantum Immune Clone Algorithm

Image Segmentation Using FCM Optimized by Quantum Immune Clo...

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International Conference on Intelligent System Design and Engineering Application (ISDEA)

作者： Yu Li Fei Tong Guojian Cheng College of Computer Science Xi'an Shiyou University of Xian Shaanxi China China Arms Industrial Company No 206 Institute Xian Shaanxi China

The traditional Fuzzy C-Means (FCM) clustering algorithm is usually based on the image intensity, so the segmentation results are unsatisfactory when the images are impacted by noise. Considering this shortcoming, in this paper the FCM objective function is improved by adding two kinds of spatial information: the relative position information and the intensity information of the neighborhood. Moreover, Quantum Immune Clone algorithm (QICA) is used to optimize the spatial impact factors in the objective function. The proposed algorithm has been tested in synthetic and real synthetic aperture radar (SAR) images segmentation. Experimental results demonstrate that the proposed algorithm is feasible and effective, and it can lead to higher accuracy.

关键词： image segmentation Clustering algorithms Linear programming Earthquakes Noise Optimization Signal processing algorithms

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A novel real-time method for high dynamic range image tone mapping

A novel real-time method for high dynamic range image tone m...

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International Conference on Information Science and Technology (ICIST)

作者： Qingquan Wu Zuofeng Zhou Hanbing Leng Jianzhong Cao Jihong Wang Zhendong Gong xinming Fan Huinan Guo Xi'an Institute of Optics and Precision Mechanics of CAS Xi'an Shaanxi Province China

Tone-mapping technique which can convert high dynamic range (HDR) to low dynamic range (LDR) images provides accurately visualization of HDR images on standard LDR displays. Most of the existing tone-mapping method could not realize real time processing while preserving good visualization. Utilizing an adaptive three-section lookup table, this paper proposes an effective, high quality, real time technique to convert 12-bit images to 8-bit image which can preserve abundant details and high contrast simultaneously. Experiment results show that this method can improve the weak signals of the image greatly, and the low luminance details can be observed distinctly on an 8-bit monitor.

关键词： Dynamic range Algorithm design and analysis Real-time systems Brightness Heuristic algorithms Educational institutions

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Hand segmentation with metric learning superpixels

Hand segmentation with metric learning superpixels

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IEEE China Summit & International Conference on Signal and Information processing (ChinaSIP)

作者： Guangdong Hou Daqing Chang Changshui Zhang State Key Laboratory of Intelligent Technologies and Systems Tsinghua National Laboratory for Information Science and Technology (TNList) Department of Automation Tsinghua University Beijing 100084 China

In this paper, we propose a novel method for hand segmentation. To improve the robustness to the wide range of hand appearances and illuminations, we segment the hand area with a superpixels based method instead of a general color model. With the exploitation of the distribution of hand pixels in color space, a distance metric learning stage is designed to promote the segmentation performance. This stage makes the points in hand areas more concentrate and pulls away from the points of background in color space. The comparisons with several widely used algorithms are made on both public available and our own datasets. The experimental results show the superior performance of our method.

关键词： image color analysis Skin Measurement image segmentation Adaptation models Covariance matrices Gesture recognition

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