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DCT Inpainting with Patch Shifting Scheme

DCT Inpainting with Patch Shifting Scheme

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2011年亚太信号与信息处理协会年会

作者： Sarawut TAE-O-SOT Akinori NISHIHARA The Department of Communications and Integrated Systems Tokyo Institute of Technology Tokyo Japan The Center for Research and Development of Educational Technology Tokyo Institute of Technology Tokyo Japan

This paper presents a novel exemplar-based image inpainting whose patch matching process is done in frequency domain in order to gain the advantage of noise reduction property. Moreover, a simple patch shifting scheme is also introduced to make sure that the target patch contains enough information to refer the unknown region. Each target patch is iteratively shifted to the position where there are enough known pixels on the patch as defined by user. This scheme can improve the traditional exemplar-based inpainting techniques which do not consider on the number of known and unknown pixels in the target patch. This ignorance can ruin the inpainting result when few known pixels are in the target patch. More meaningful target patches are provided by the proposed scheme. Experimental results show a significant improvement from traditional exemplar-based approach in both visual and mathematical aspects. Sharper and more continuous edge can be achieved by our approach.

关键词： image DCT Inpainting with Patch Shifting Scheme Criminisi

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Classification of the Type of Brain Tumor in MRI Using Xception Model

Classification of the Type of Brain Tumor in MRI Using Xcept...

引用

International conference on Electronics, Information and communications (ICEIC)

作者： Ramil Cobilla Jhon Carlo Dichoso Alexandre Benedict Miñon April Kate Pascual Mideth Abisado Shekinah Lor Huyo-a Gabriel Avelino Sampedro College of Computer Science Technological University of the Philippines Manila Philippines College of Computing and Information Technologies National University Manila Philippines Research and Development Center Philippine Coding Camp Manila Philippines Faculty of Information and Communication Studies University of the Philippines Open University Laguna Philippines

A brain tumor is recognized as one of the most invasive things to operate on. Cancer develops inside the brain due to unregulated and aberrant cell partitioning. The recent breakthroughs in deep learning greatly aided the medical imaging sector in diagnosing numerous diseases. In MR images, visual learning and image recognition have been used to classify the type of brain tumor. The researchers utilized a Convolutional Neural Network (CNN) approach, Data Augmentation, and image processing to organize brain MRI scans as cancerous or non-cancerous. Using the transfer learning method, the researchers compared the performance of the primary CNN model to that of pre-trained CNN and Xception models. However, the experiment was conducted on a limited dataset. Later results reveal that the model’s accuracy result is very effective and has a meager complexity rate, attaining 96% accuracy on the Xception Model.

关键词： Deep learning visualization image recognition Magnetic resonance imaging Transfer learning Brain modeling Complexity theory

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image processing for Error Concealment

Image Processing for Error Concealment

引用

Mexican International conference on Artificial Intelligence, MICAI

作者： Mireya S. Garcia-V´zquez Abril F. Garcia-Ramirez Alejandro A. Ramirez-Acosta Centro de Investigación y Desarollo de Tecnología Digital CITEDI Tijuana Baja California México C.P. MIRALR&D Imperial Beach Imperial Beach USA

Transmission of videos in error prone environments such as mobile communications, may lead to video corruption or loss so that received visual quality is degraded. Therefore, it is essential to implement efficient and low complexity error concealment methods which allow visually reducing the degradation caused by the missing information. The contribution of this work is to report the results of a comparative analysis of five temporal error concealment (TEC) techniques in critical situations, where the frames are corrupted with different errors pattern covering 50% of the image area. The results indicate, according to two similarity metrics (SAD-BM and SAD-OBM), that the 'Best motion vector neighbor' and 'Zero motion vector' are the best TEC options. These results could help in the development of a robust but simple TEC algorithm against several errors distribution. This could be valuable in mobile video applications in which user's video requests are becoming more and more demanding and therefore significant loss of information could be present due to node congestion or excessive delay.

关键词： Vectors Measurement Videos Statistical analysis Mobile communication image reconstruction Correlation

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DnM3Net: Multi-Scale & Multi-Level Shuffle-CNN Via Multi-Level Attention for image Denoising

DnM3Net: Multi-Scale & Multi-Level Shuffle-CNN Via Multi-Lev...

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IEEE International Symposium on Parallel and Distributed processing with Applications and IEEE International conference on Ubiquitous Computing and communications (ISPA/IUCC)

作者： Yue Cao Jinhe He Yu Zhang Gang Lu Shigang Liu Xiaojun Wu School of Computer Science Shaanxi Normal University Xian Shaanxi Normal University Xi'an China

ISBN: (纸本)9781728152103

Recently, based on novel convolutional neural net-work architectures proposed, tremendous advances have been achieved in image denoising task. An effective and efficient multi-level network architecture for image denoising refers to restore the latent clean image from a coarser scale to finer scales and pass features through multiple levels of the model. Unfortunately, the bottleneck of applying multi-level network architecture lies in the multi-scale information from input images is not effectively captured and the fine-to-coarse feature fusion strategy to be ignored in image denoising task. To solve these problems, we propose a multi-scale & multi-level shuffle-CNN Via multi-level attention (DnM3Net), which plugs the multi-scale feature extraction, fine-to-coarse feature fusion strategy and multi-level attention module into the new network architecture in image denoising task. The advantage of this approach are two-fold: (1) It solve the multi-scale information extraction issue of multi-level network architecture, making it more effective and efficient for the image denoising task. (2) It is impressive performance because the better trade-off between denoising and detail preservation. The proposed novel network architecture is validated by applying on synthetic gaussian noise gray and RGB images. Experimental results show that the DnM3Net effectively improve the quantitative metrics and visual quality compared to the state-of-the-art denoising methods.

关键词： convolutional neural nets feature extraction Gaussian noise image colour analysis image denoising image sampling image denoising image samples image colour analysis NETWORK STRUCTURE Gaussian noise Feature extraction multi-scale hierarchical models Noise reduction

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visual correlation-based image gathering for wireless multimedia sensor networks

Visual correlation-based image gathering for wireless multim...

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IEEE Annual Joint conference: INFOCOM, IEEE Computer and communications Societies

作者： Pu Wang Rui Dai Ian F. Akyildiz Broadband Wireless Networking Laboratory School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)9781424499199

In wireless multimedia sensor networks (WMSNs), visual correlation exist among multiple nearby cameras, thus leading to considerable redundancy in the collected images. This paper addresses the problem of timely and efficiently gathering visually correlated images from camera sensors. Towards this, three fundamental problems are considered, namely, MinMax Degree Hub Location (MDHL), Minimum Sum-entropy Camera Assignment (MSCA), and Maximum Lifetime Scheduling (MLS). The MDHL problem aims to find the optimal locations to place the multimedia processing hubs, which operate on different channels for concurrently collecting images from adjacent cameras, such that the number of channels required for frequency reuse is minimized. With the locations of the hubs determined by the MDHL problem, the objective of the MSCA problem is to assign each camera to a hub in such a way that the global compression gain is maximized by jointly encoding the visually correlated images gathered by each hub. At last, given a hub and its associated cameras, the MLS problem targets at designing a schedule for the cameras such that the network lifetime of the cameras is maximized by letting highly correlated cameras perform differential coding on the fly. It is proven in this paper that the MDHL problem is NP-complete, and the others are NP-hard. Consequently, approximation and heuristic algorithms are proposed. Since the designed algorithms only take the camera settings as inputs, they are independent of specific multimedia applications. Experiments and simulations show that the proposed image gathering schemes effectively enhance network throughput and image compression performance.

关键词： Cameras Joints Entropy image coding Encoding visualization Correlation

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Visibility Estimation of Traffic Signals under Rainy Weather Conditions for Smart Driving Support

Visibility Estimation of Traffic Signals under Rainy Weather...

引用

International IEEE conference on Intelligent Transportation Systems

作者： Ryuhei Sato Keisuke Doman Daisuke Deguchi Yoshito Mekada Ichiro Ide Hiroshi Murase Yukimasa Tamatsu Graduate School of Information Science Nagoya University Japan Society for the Promotion of Science Information and Communications Headquarters Nagoya University School of Information Science & Technology Chukyo University DENSO CORPORATION

ISBN: (纸本)9781467330640

The aim of this work is to support a driver by notifying the information of traffic signals in accordance with their visibility. To avoid traffic accidents, the driver should detect and recognize surrounding objects, especially traffic signals. However, when driving a vehicle under rainy weather conditions, it is difficult for drivers to detect or to recognize objects existing in the road environment in comparison with fine weather conditions. Therefore, this paper proposes a method for estimating the visibility of traffic signals for drivers under rainy weather conditions by image processing. The proposed method is based on the concept of visual noise known in the field of cognitive science, and extracts two types of visual noise features which ware considered that they affect the visibility of traffic signals. We expect to improve the accuracy of visibility estimation by combining the visual noise features with the texture feature introduced in a previous work. Experimental results showed that the proposed method could estimate the visibility of traffic signals more accurately under rainy weather conditions.

关键词： Meteorology visualization Noise Vehicles Estimation Cameras Accuracy

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Watermarking compressed video stream over Internet

Watermarking compressed video stream over Internet

引用

Asia-Pacific conference on communications

作者： D. Ghosh K. Ramakrishna Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati India Digital Signal Processing Group Emuzed India Private Limited Bangalore India

As Internet is gaining popularity day by day throughout the globe, it has become necessary to protect the copyright ownership of multimedia data distributing in Internet. The technique generally used for the purpose is watermarking. This has motivated the ongoing research in watermarking. In this paper, we develop an oblivious scheme for watermarking MPEG coded video stream over Internet. The inter-frame similarity present in a video sequence is exploited to calculate the watermark to be embedded. Watermark corresponding to a region in the current frame is obtained from its best match in the previous frame. The watermark is embedded during the coding process thereby keeping the overall computational overhead minimum. The algorithm has been tested in terms of the watermarked video quality and its capability in extracting the author's signature (watermark bits). We have also tested the robustness of the proposed scheme against noise attack. Results obtained demonstrate the efficiency of the proposed method.

关键词： Watermarking Video compression Streaming media Internet Protection Testing image coding Robustness Frequency domain analysis Wavelet transforms

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A role of burst firings of hindbrain neurons in detecting object distance in electrolocation

A role of burst firings of hindbrain neurons in detecting ob...

引用

International conference on Neural Information processing

作者： E. Murase Y. Kashimori MeiHong Zheng T. Kambara Department of Information Network Science School of Information Systems Division of Bioinfomatics University of Electro-Communications Chofu Tokyo Japan

Weakly electric fish generates electric field around its body using electric organ discharge and can accurately detect the location of an object using the modulation of electric field induced by an object. Objects with electric properties different from those of the surrounding water distort the electric field around fish's body depending on the size, distance and electric properties of objects. It is not clear yet how the fish recognizes the properties of an object such as its electric property, location and size based on its electric image. As the first step to clarify the neuronal mechanism of electrolocation, we developed a model of fish body by which we describe numerically the spatio-temporal patterns of electric field around the fish body. We made also neural models of electroreceptors distributed on the fish body and of electrosensory lateral line lobe (ELL) to investigate what kinds of information of electric field distorted by an object they detect. The models reproduce qualitatively the experimental results about the detections of size, distance, and moving directions of an object. We show that the lateral distance between a moving object and fish is encoded by the synchronous burst firing of ELL neurons, reflecting the spatio-temporal correlations of EOD stimuli received by the receptors.

关键词： Neurons Object detection Marine animals Brain modeling Intelligent networks Fault location visual system Auditory system Signal processing Voltage

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ViEdge: An Edge-based Platform for Video Analytics Applications in Smart Estates

ViEdge: An Edge-based Platform for Video Analytics Applicati...

引用

International conference on Computer communications and Networks (ICCCN)

作者： Vishal Choudhary Rahul Aggarwal Hock Beng Lim Binbin Chen Center for Smart Systems (CS2) Singapore University of Technology and Design Singapore Information Systems Technology and Design Pillar (ISTD) Singapore University of Technology and Design Singapore

ISBN: (数字)9798350384611

ISBN: (纸本)9798350348439

Video analytics plays a crucial role in the development of smart estates and cities. Applications such as garbage dumping detection, lift monitoring, safety surveillance, etc. rely on video analytics, and require fast response time. Traditional cloud-based systems are ill-suited for these applications due to their limitations in handling large volume of video data with low latency. In contrast, the IoT-Edge-Cloud paradigm is better suited for such applications, but it presents challenges such as system heterogeneity, and resource allocation and orchestration. There is a need for an efficient platform for distributed video stream processing where resource orchestration and scalability aspects are tailored to smart estate *** this paper, we present ViEdge, an edge-based platform for video analytics applications in smart estates. It is highly adaptable and scalable, making it ideal for various deployments in such environments. Our implementation of ViEdge utilizes Kubernetes (K8s) for resource management and orchestration, and Apache Storm for distributed video stream processing. To study ViEdge’s customization capabilities, we evaluated its performance on a heterogeneous edge testbed. We observed increased latency in Apache Storm when integrated with Kubernetes, affecting overall application performance. However, by developing a heuristic-based scheduler, we demonstrate that ViEdge effectively reduces end-to-end latency and enhances frame processing rates.

关键词： Storms visual analytics Surveillance image edge detection Urban areas Streaming media Safety

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A Real-time Full-HD 2D-to-3D Conversion System Using Multicore Technology

A Real-time Full-HD 2D-to-3D Conversion System Using Multico...

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International conference on Multimedia and Ubiquitous Engineering (MUE)

作者： Ching-Lung Su Kang-Ning Pang Tse-Min Chen Guo-Syuan Wu Chia-Ling Chiang Hang-Rnei Wen Lung-Sheng Huang Ya-Hsin Hsueh Shau-Yin Tseng SoC Lab Department of Electronics Engineering National Yunlin University of Science and Technology Yunlin Taiwan Division for Embedded System and SoC Information and Communications Research Laboratories ITRI Hsinchu Taiwan

The advancement of visual technology and the maturity of display process technique enable monitor industry to put forth multi-view stereo display systems, which allow consumers to watch 3D images with naked eyes. However, due to the insufficient 3D original videos, we are unable to achieve the end of enjoying 3D effect through stereo display. Therefore, this paper aims to provide a real-time algorithm for 2D-to-3D conversion, through which 2D video will be accompanied with a depth image so that one can obtain 3D images through auto stereoscopic display. The proposed algorithm focuses on the depth of background scenes and the active objects, while extracting depth information from the two for complete processing of depth generation. Since the production of depth information always requires heavy computation, we adapt VIA's embedded systems with a 1.6GHz CPU, as well as nVIDIA CUDA (compute unified device architecture) technology which contains 256 core processor with the clock rate of each processor up to 950MHz. When accompanied with our proposed CUDA parallelization technique, the experimental results show an 83% of recognition rate for depth image, and a display rate of 32.52 frames per second in Full-HD format (1920×1088 pixels).

关键词： Three dimensional displays Graphics processing unit Videos Real time systems Instruction sets image color analysis image edge detection

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