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Rate scalable video coding using a foveation-based human visual system model

Rate scalable video coding using a foveation-based human vis...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Zhou Wang Ligang Lu A.C. Bovik Laboratory for Image and Video Engineering LIVE Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA Video and Image Systems IBM Thomas J. Watson Research Center Yorktown Heights NY USA

Recently, there have been two interesting trends in image and video coding research. One is to use human visual system (HVS) models to improve the current state-of-the-art coding algorithms by better exploiting the properties of the intended receiver. The other is to design rate-scalable video codecs, which allow the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream. We follow these two trends and propose a foveation scalable video coding (FSVC) algorithm, which supplies good quality-compression performance as well as effective rate scalability to support simple and precise bit rate control. A foveation-based HVS model plays a key role in the algorithm. The algorithm is amenable to the inclusion of various HVS models and adaptable to different video communication applications.

关键词： Video coding Humans Visual system Video compression image coding Partitioning algorithms Bit rate Scalability Bandwidth Discrete wavelet transforms

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Using image processing on MRI Scans

Using Image Processing on MRI Scans

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IEEE International conference on signal processing, Informatics, Communication and Energy Systems (SPICES)

作者： Chetan Patil M G Mathura S Madhumitha S Sumam David Merwyn Fernandes Anand Venugopal B. Unnikrishnan Dept. of E&C NITK Surathkal Mangalore 575025 India Dept. of Radiology Kasturba Medical College Mangalore 575001 India Dept. of Community Medicine Kasturba Medical College Mangalore 575001 India

Alzheimer's disease (AD) is an irreversible and progressive brain disease that gradually destroys memory and thinking skills to an extent that it starts affecting the daily life. It has become the most common cause of dementia among older people. The work presented in this paper evaluates the utility of image processing on the Magnetic Resonance Imaging (MRI) scans to estimate the possibility of an early detection of AD. The total brain atrophy and specifically the hippocampal atrophy are considered strong diagnostic tests for AD. T1 weighted MRIs have been used for the purpose of image processing to evaluate atrophy. The paper demonstrates the applications of several image processing techniques such as K-means clustering, wavelet transform, watershed algorithm and also a customized algorithm tailored for the specific case. It has been implemented on the open source platforms, OpenCV and Qt, which facilitates the implementation and utility of the developed product in the hospitals without requiring any proprietary software. The results obtained from the project could aid the analysis to detect AD along with correlation with the psychiatric results and could thus assist the doctors in detecting AD at an early stage. This could progressively help in understanding and treating AD.

关键词： Atrophy Magnetic resonance imaging Alzheimer's disease Hippocampus Medical diagnostic imaging

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Detection of Detonators in Baggage Using Deep CNN Architecture: A Comparative Study of Contrast Enhancement and Feature Extraction Methods

Detection of Detonators in Baggage Using Deep CNN Architectu...

引用

International conference on image and signal processing and their applications (ISPA)

作者： Oulhissane Lynda Merah Mostefa Simona Moldovanu Luminita Moraru Laboratory of Signals and Systems LSS Faculty of Science and Technology Abdelhamid Ibn Badis University Mostaganem Algeria MSlab Department of Computer Science and Information Technology Modelling & Simulation Laboratory Faculty of Automation Computers Electrical Engineering and Electronics Dunarea de Jos University of Galati Galati Romania MSlab Department of Chemistry Physics & Environment Modelling & Simulation Laboratory Faculty of Sciences and Environment Dunarea de Jos University of Galati Galati Romania

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

Visual inspection of dual-energy X-ray radiographic images of cabin baggage requires high performance, but is hindered by various challenges such as low target prevalence, variability in target visibility, possible presence of multiple targets, and security personnel fatigue and inattention. Artificial intelligence (AI) techniques, particularly deep convolutional neural networks (CNNs), have shown promise in improving the automatic detection of explosives, even with low-resolution radiographic images, especially in high baggage throughput scenarios. In this paper, we focus on the detection of detonators as components of improvised explosive devices. The proposed approach involves comparing two experiments implemented in a deep CNN architecture using TensorFlow and Keras libraries. In the first experiment, raw dual-energy radiographic images without any enhancement were used. The second experiment includes three methods for contrast enhancement and feature extraction: the Contrast Limited Adaptive Histogram Equalization (CLAHE) method, the wavelet transform-based method, and the mixed CLAHE RGB-wavelet method. In the latter two methods, Haar, Db2, Coif2, and Sym2 mother wavelet functions at two levels (HH and HL) were employed. The analysis of results focuses on a comparative study of performance measures such as accuracy, precision, recall, and F1 score. It was found that the preprocessing methods used in experiment 2, for the two evaluated classes (detonator and no detonator), achieved higher accuracy compared to the raw radiographic images used in experiment 1 (98.08%). The highest accuracies in experiment 2, with a value of 100%, were obtained with the CLAHE method (green channel in grayscale, blue channel in grayscale, and RGB channels) and the wavelet transform method with Haar mother wavelet at two levels HL

关键词： wavelet transforms Radiography Visualization Gray-scale Inspection Feature extraction Libraries

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Multi-Rate signal processing with the Use of Filter Banks Composed of Parallel FIR Filters

Multi-Rate Signal Processing with the Use of Filter Banks Co...

引用

International conference on Microelectronics, MIEL

作者： M. Banach R. Długosz Poznan University of Technology Institute of Architecture and Spatial Planning Nieszawska 13C Poznań Poland Aptiv Services Poland ul. Podgórki Tynieckie 2 Kraków Poland

The paper presents a concept of a hardware implementation of 2-D finite impulse response (FIR) filter banks for the application in image processing and analysis. Banks composed of low-and high-pass FIR filters are basic components of multi-stage discrete wavelet transform (DWT). The applications of such solutions that are in the scope of our interests are vision systems used in automotive active safety functions (e.g in line departure warning). Basics of the DWT are broadly described in the literature. In our work we focus on solutions supporting hardware realization of filter banks for DWT. The proposed parallel and asynchronous circuits allow to achieve the processing time for a single pixel not exceeding 2 to 4 ns, depending on the size of the mask (data for TSMC 180 nm CMOS process).

关键词： Discrete wavelet transforms Finite impulse response filters Hardware Frequency response Complexity theory

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SAR image despeckling using undecimated directional filter banks and mean shift

SAR image despeckling using undecimated directional filter b...

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IEEE International conference on image processing

作者： Gong Zhang Wenhua Shi Jing Xu Ning Li Mark J. T. Smith College of Information Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

The granular appearance of speckle noise in synthetic aperture radar (SAR) imagery can make it difficult to visually and automatically interpret SAR data. Speckle reduction is a prerequisite for many SAR image processing tasks. In this paper, a novel method of SAR image despeckling is presented that uses undecimated directional filter banks (UDFB) and mean shift clustering. The UDFB is obtained by manipulating the resampling matrices in the Bamberger directional filter banks (DFB), such that low computational complexity is preserved, while achieving shift invariance that could be useful in pattern recognition and image denoising applications. A nonparametric estimator of the density gradient is employed in the joint spatial-range domain of the directional bands obtained by the UDFB. Examples included at the end of the paper illustrate typical performance results obtained using this method.

关键词： Filter bank Speckle Discrete wavelet transforms Filtering image analysis Synthetic aperture radar signal analysis Channel bank filters Educational institutions Information science

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A computational vision approach to image registration

A computational vision approach to image registration

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International conference on Pattern Recognition

作者： Q. Zheng R. Chellappa Signal and Image Processing Institute University of Southern California Los Angeles CA USA Department of Electrical Engineering Center for Automation Research University of Maryland College Park MD USA

Automatic image registration is important for many multiframe-based image analysis applications. In this paper, a computational vision approach is presented for the estimation of 2-D translation, rotation, and scale from two partially overlapping images. The approach has the following features: (1) an illuminant direction estimator is used to obtain an initial estimate of camera rotation; (2) feature points are located based on a Gabor wavelet model for detecting local curvature discontinuities; (3) estimation of rotation and translation is formulated as a linear problem; and (4) hierarchical coarse-to-fine matching is used. This results in a fast and novel algorithm that produces good results even when large rotations and scale changes have occurred between the two frames and the images are devoid of significant features. Several applications of the algorithm are presented.< >

关键词： Computer vision image registration Cameras Motion estimation Object detection image motion analysis Robustness Feature extraction Forward contracts Coordinate measuring machines

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The Coronary Atherosclerosis Detection: A Diagnostic Approach of Digital Electrocardiography image Interpretation

The Coronary Atherosclerosis Detection: A Diagnostic Approac...

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Data Science and Its applications (ICoDSA), International conference on

作者： Firna Yenila Yuhandri Okfalisa Information System Department Universitas Putra Indonesia YPTK Padang Indonesia Information Technology Department Universitas Putra Indonesia YPTK Padang Indonesia Universitas Islam Negeri Sultan Syarif Kasim Riau Indonesia

ISBN: (数字)9798350365351

ISBN: (纸本)9798350365368

Coronary Atherosclerosis is recognized as the predominant cause of Chronic Heart Failure. The standard diagnostic modality for Coronary Atherosclerosis involves echocardiography (ECO); however, the accessibility of such diagnostic equipment remains constrained within several healthcare facilities. Consequently, there is a demand for a more straightforward diagnostic approach, specifically through the utilization of Electrocardiography (ECG). This investigation endeavors to introduce an automated methodology for the detection of Coronary Atherosclerosis, enhancing the precision of ECG interpretation via digital imaging predicated on cardiac signal detection graphs obtained through this modality. The algorithm employed to delineate the ECG signal dynamics for the diagnostic identification of Coronary Atherosclerosis is the Continuous wavelet Transform (CWT). The application of CWT follows the execution of multiple pre-processing phases on the ECG signal graph, including image cropping to isolate the graph within the ECG and segmentation to eliminate background interference, thereby concentrating on the graph for subsequent analysis. This preprocessing facilitates the interpretative process through the CWT algorithm. The analysis proceeds with a classification phase employing a Convolutional Neural Network (CNN), which differentiates between normal patient conditions and those presenting with Coronary Atherosclerosis and normal ECG. The experimental outcomes derived from the application of the proposed algorithm demonstrate a significant enhancement in the accuracy of ECG interpretation, achieving a diagnostic accuracy rate of 96% for the detection of Coronary Atherosclerosis.

关键词： image segmentation Continuous wavelet transforms Accuracy Echocardiography Heuristic algorithms Atherosclerosis Electrocardiography

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Indexing spatial content of still texture in MPEG-4

Indexing spatial content of still texture in MPEG-4

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European signal processing conference (EUSIPCO)

作者： Jayank Bhalod V Mohammed Zubair S. Panchanathan Visual Computing and Communications Laboratory Department of Computer Science and Engineering Arizona State University Tempe - Arizona USA

There has been a rapid increase in audio-visual information in digital form with the ever-increasing popularity of the Internet. The Moving Pictures Expert Group has recently presented a video compression and content manipulation standard, called MPEG-4 [1]. This was developed in response to the growing need for a coding method that can facilitate access to visual objects in natural and synthetic moving pictures in a wide variety of applications. In this paper, we propose a method for indexing the spatial content of Still Texture in MPEG-4 Video. There has been a number of approaches proposed recently [1],[3],[5],[6], which address content based indexing using features such as, color, shape and/or texture. We note that the still texture information is encoded using wavelet Transform in MPEG-4. Since still texture can have an arbitrary shape, we propose to employ a combination of shape, color and texture features. The shape features are derived from the alpha plane and represented using Cubic B-spline approximation. The color and texture features are extracted directly from the wavelet compressed domain. An important attribute of the proposed approach is also the introduction of the novel concept of “containment” of spatial features for content based indexing.

关键词： Shape image color analysis Transform coding Indexing Splines (mathematics) Feature extraction Vectors

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Scalable coding and progressive transmission of concentric mosaic using nonlinear filter banks

Scalable coding and progressive transmission of concentric m...

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IEEE International conference on image processing

作者： King-To Ng Shing-Chow Chan Heung-Yeung Shun Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong China Microsoft Research Limited USA

ISBN: (纸本)0780367251

This paper studies the scalable coding and progressive transmission of concentric mosaic to support interactive applications over a LAN or the Internet. Concentric mosaic is an effective 3D image based representation of a static scene. A typical concentric mosaic might consist of thousands of images, which poses significant problem in digital storage and transmission. A new multiresolution decomposition for supporting progressive transmission of a concentric mosaic is proposed. Instead of using the popular 9/7 wavelet filterbank, a nonlinear perfect reconstruction filter bank with lower arithmetic complexity is employed. It also considerably simplifies the random access operation of the slit images during rendering. By encoding the subband signals into different layers, a scalable compressed bit stream of the concentric mosaic is obtained. Therefore, progressive transmission of concentric mosaic, using a combination of these layers, to support devices with different capabilities become possible.

关键词： image storage Filter bank Local area networks Internet Layout signal resolution image reconstruction Arithmetic Rendering (computer graphics) Encoding

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A Review on Digital image Watermarking Using Transformation and Optimization Techniques

A Review on Digital Image Watermarking Using Transformation ...

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International conference on Advances in Computing, Communication Control and Networking (ICACCCN)

作者： Lalita Verma Sanjay Pratap Singh Chauhan School of Computer Science and Engineering Galgotias University Greater Noida India

ISBN: (数字)9781728183374

ISBN: (纸本)9781728183381

Now-a-days multimedia data is being generated very frequently in text format, image format, audio format etc. Security is the major issue of the multimedia data. Multimedia data can be very easily modified by the intruders. By using Watermarking and Steganography techniques the multimedia data can be protected from unauthorised access. Watermarking technique hides the data in the carrier signal. In the process of Steganography, the digital data (e.g. digital files like audio, video, text etc) can be embedded into some other digital file. The concept of watermarking is to keep the watermark robust from various attacks. Whenever the intruder tries to temper with the digital signal and removes the watermark, the digital data becomes useless as the quality is degraded. This paper discusses about various applications of watermarking, characteristics of Watermarking and basics of image processing. This paper also provides a comprehensive study of available literature on digital image watermarking. Some of the optimization techniques have also been discussed.

关键词： wavelet transforms Digital images image processing Watermarking Streaming media Optimization

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