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A multiresolution DCT-based blind blur quality measure 7

A multiresolution DCT-based blind blur quality measure

引用

7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Kerouh, Fatma Ziou, Djemel Serir, Amina Univ Sherbrooke Fac Sci Quebec City PQ Canada Univ Sci & Technol Houari Boumediene Fac Elect & Informat Algiers Algeria

ISBN: (纸本)9781538618424

The paper deals with assessing blur amount in images. Blur is a common artefact that attenuates the high frequency components of an image. The main idea turns on analysing the frequency response at transitions through resolutions. To achieve that, the histogram of the multiresolution DCT coefficients is modelled by using an exponential probability density function (pdf). The steepness of the pdf is used as a cue to characterize the blur effect. Faithful scores are obtained while testing the proposed approach on five image collections. The proposed measure is validated on the JPEG2000 lossy compression algorithm and the Lucy-Richardson iterative deblurring approach.

关键词： Blind image quality blur high frequencies analysis probability density function

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Illumination-robust multispectral demosaicing 7

Illumination-robust multispectral demosaicing

引用

7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Mihoubi, Sofiane Mathon, Benjamin Thomas, Jean-Baptiste Losson, Olivier Macaire, Ludovic Univ Lille CRIStAL Ctr Rech Informat Signal & Automat Lille CNRS Cent LilleUMR 9189 F-59000 Lille France Univ Bourgogne Franche Comte FRE CNRS 2005 Le2i F-21000 Dijon France Norwegian Univ Sci & Technol Norwegian Colour & Visual Comp Lab Gjovik Norway

ISBN: (纸本)9781538618424

Snapshot multispectral cameras that are equipped with filter arrays acquire a raw image that represents the radiance of a scene over the electromagnetic spectrum at video rate. These cameras require a demosaicing procedure to estimate a multispectral image with full spatio-spectral definition. Such a procedure is based on spectral correlation properties that are sensitive to illumination. In this paper, we first highlight the influence of illumination on demosaicing performances. Then we propose camera-, illumination-, and raw image-based normalisations that make demosaicing robust to illumination. Experimental results on state-of-the-art demosaicing algorithms show that such normalisations improve the quality of multispectral images estimated from raw images acquired under various illuminations.

关键词： image demosaicing Multispectral filter array Illumination Spectral correlation Snapshot camera

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Dynamic Optimization of Mental Workload in fNIRS-BCI System for Cognitive Rehabilitation 5

Dynamic Optimization of Mental Workload in fNIRS-BCI System ...

引用

IEEE International conference on signal and image processing applications (ICSIPA)

作者： Ung, W. C. Tang, T. B. Meriaudeau, F. Ebenezer, E. G. M. Univ Teknol PETRONAS Ctr Intelligent Signal & Imaging Res Dept Elect & Elect Engn Bandar Seri Iskandar Perak Malaysia Univ Kuala Lumpur Royal Coll Med Perak Med Based Dept Ipoh Perak Malaysia

ISBN: (纸本)9781509055593

Cognitive rehabilitation has been proposed as an alternative treatment for Alzheimer's disease (AD) as it helps to preserve brain functionality. However, gains of cognitive training or rehabilitation may be eliminated due to cognitive overload and mental fatigue. This paper reports the development of a functional near-infrared spectroscopy (fNIRS) - brain-computer interface (BCI) that can adjust task difficulty adaptively. The aim is to have participants trained at their optimal level of difficulty and workload to maximize their gains. One patient with mild AD and one healthy control were recruited to test the functionality of proposed fNIRS-BCI system. The fNIRS-BCI system is able to process fNIRS signals in real time and adjust task difficulty accordingly. The healthy control was able to proceed to higher task levels, as compared to the mild AD patient. The fNIRS-BCI system has the potential as a tool to examine the efficacy of cognitive rehabilitation as an alternative treatment for AD.

关键词： Alzheimer's disease cognitive rehabilitation functional near-infrared spectroscopy brain-computer interface fNIRS-BCI

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Local Radon Descriptors for image Search 7

Local Radon Descriptors for Image Search

引用

7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Babaie, Morteza Tizhoosh, H. R. Khatami, Amin Shiri, M. E. Amirkabir Univ Technol Dept Math & Comp Sci Tehran Iran Univ Waterloo KIMIA Lab Waterloo ON Canada Deakin Univ IISRI Geelong Vic Australia

ISBN: (纸本)9781538618424

Radon transform and its inverse operation are important techniques in medical imaging tasks. Recently, there has been renewed interest in Radon transform for applications such as content-based medical image retrieval. However, all studies so far have used Radon transform as a global or quasi global image descriptor by extracting projections of the whole image or large sub-images. This paper attempts to show that the dense sampling to generate the histogram of local Radon projections has a much higher discrimination capability than the global one. In this paper, we introduce Local Radon Descriptor (LRD) and apply it to the IRMA dataset, which contains 14,410 x-ray images as well as to the INRIA Holidays dataset with 1,990 images. Our results show significant improvement in retrieval performance by using LRD versus its global version. We also demonstrate that LRD can deliver results comparable to well established descriptors like LBP and HOG.

关键词： image retrieval image descriptor Radon projections local projections IRMA dataset

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No-reference image quality assessment using Gabor-based smoothness and latent noise estimation 7

No-reference image quality assessment using Gabor-based smoo...

引用

7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Kumar, Vineet Chouhan, Rajlaxmi Indian Inst Technol Dept Elect Engn Jodhpur Rajasthan India

ISBN: (纸本)9781538618424

No-reference image quality assessment is a challenging task due to the absence of a reference image in practical situations to quantify image quality. This paper proposes a new no-reference image quality metric for natural images using latent noise estimation, Gabor response, and contrast deviation. The algorithm employs an extension of gradient-based SSIM into the no-reference application using SVD-based AWGN estimation, and defines attributes such as Gabor-based smoothness and contrast deviation. The proposed metric arrives at an overall quality score by computing a linear weighted summation of the three image attributes. The proposed algorithm has been tested on several public databases (i.e. LIVE, TID 2013 and CSIQ), and the overall results display a noteworthy correlation of nearly 80% with the human visual system.

关键词： Measurement image quality AWGN Indexes Distortion Estimation Visual systems

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Total Variation Iterative Linear Expansion of Thresholds with applications in CT

Total Variation Iterative Linear Expansion of Thresholds wit...

引用

IEEE International conference on Acoustics, Speech and signal processing

作者： Shahar Tsiper Oren Solomon Yonina C. Eldar Technion -- Israel Institute of Technology

ISBN: (纸本)9781538646595

The iterative linear expansion of threshold framework, or iLET, offers a new approach for solving image restoration problems under sparsity assumptions. Instead of estimating the reconstructed image directly, the iLET paradigm parametrizes the reconstruction process as a linear combination of elementary thresholding functions and optimizes over their coefficients. Here, we rely on the fast and accurate convergence of iLET, and propose an extension of this framework, under the assumption that the reconstructed object is approximately piece-wise constant. This assumption leads to a new total-variation framework of iLET. We demonstrate the applicability of our technique to bio-medical imaging problems, such as computerized tomography reconstruction. Our technique surpasses state-of-the-art reconstructions in terms of PSNR and SSIM, while offering an automatic way for tuning its regularization parameter.

关键词： Total Variation Sparse Recovery Convex Optimization Computed Tomography x-Ray Computed Tomography Convex function Threshold Reconstructive Surgical Procedures Frameworks Peak signal-to-noise ratio image restoration technique Linear Combination

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Footnote-based Document image Classification using 1D Convolutional Neural Networks and Histograms 7

Footnote-based Document Image Classification using 1D Convol...

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7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Mhiri, Mohamed Abuelwafa, Sherif Desrosiers, Christian Cheriet, Mohamed ETS Montreal PQ Canada

ISBN: (纸本)9781538618424

Classifying historical document images is a challenging task due to the high variability of their content and the common presence of degradation in these documents. For scholars, footnotes are essential to analyze and investigate historical documents. In this work, a novel classification method is proposed for detecting and segmenting footnotes from document images. Our proposed method utilizes horizontal histograms of text lines as inputs to a 1D Convolutional Neural Network (CNN). Experiments on a dataset of historical documents show the proposed method to be effective in dealing with the high variability of footnotes, even while using a small training set. Our method yielded an overall F-measure of 5636% and a precision of 89.76 %, outperforming significantly existing approaches for this task.

关键词： Footnote detection Histograms classification 1D Convolutional neural network

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Multimodal three-dimensional vision for wildland fires detection and analysis 7

Multimodal three-dimensional vision for wildland fires detec...

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7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Akhloufi, M. A. Toulouse, T. Rossi, L. Maldague, x. Univ Moncton Dept Comp Sci Moncton NB Canada Univ Corsica UMR CNRS SPE 6134 Corte France Laval Univ Elect Comp Engn Quebec City PQ Canada

ISBN: (纸本)9781538618424

This paper proposes a new multimodal stereovision framework for wildland fires detection and analysis. The proposed system uses near infrared and visible images to robustly segment the fires and extract their three-dimensional characteristics during propagation It uses multiple multimodal stereovision systems to capture complementary views of the fire front. A new registration approach is proposed, it uses multisensory fusion based on GNSS and IMU data to extract the projection matrix that permits the representation of the 3D reconstructed fire in a common reference frame. The fire parameters are extracted in 3D space during fire propagation using the complete reconstructed fire. The obtained results show the efficiency of the proposed system for wildland fires research and firefighting decision support in operational scenarios.

关键词： Multimodal vision infrared imaging wildland fires image processing 3D vision

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Detecting exercise-induced fatigue using thermal imaging and deep learning 7

Detecting exercise-induced fatigue using thermal imaging and...

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7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Lopez, Miguel Bordallo del-Blanco, Carlos R. Garcia, Narciso Univ Oulu Ctr Machine Vis & Signal Anal Oulu Finland Univ Politecn Madrid ETSI Telecomunicac Grp Tratamiento Imagenes Madrid Spain

ISBN: (纸本)9781538618424

Fatigue has adverse effects in both physical and cognitive abilities. Hence, automatically detecting exercise-induced fatigue is of importance, especially in order to assist in the planning of effort and resting during exercise sessions. Thermal imaging and facial analysis provide a mean to detect changes in the human body unobtrusively and in variant conditions of pose and illumination. In this context, this paper proposes the automatic detection of exercise-induced fatigue using thermal cameras and facial images, analyzing them using deep convolutional neural networks. Our results indicate that classification of fatigued individuals is possible, obtaining an accuracy that reaches over 80% when utilizing single thermal images.

关键词： Fatigue detection facial expression deep learning thermal imaging

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Enlarging the Discriminability of Bag-of-Words Representations with Deep Convolutional Features 7

Enlarging the Discriminability of Bag-of-Words Representatio...

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7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Manger, Daniel Willersinn, Dieter Fraunhofer IOSB Karlsruhe Germany

ISBN: (纸本)9781538618424

In this work, we propose an extension of established image retrieval models which are based on the bag-of-words representation, i.e. on models which quantize local features such as SIFT to leverage an inverted file indexing scheme for speedup. Since the quantization of local features impairs their discriminability, the ability to retrieve those database images which show the same object or scene to a given query image is decreasing with the growing number of images in the database. We address this issue by extending a quantized local feature with information from its local spatial neighborhood incorporating a representation based on pooling features from deep convolutional neural network layer outputs. Using four public datasets, we evaluate both the discriminability of the representation and its overall performance in a large-scale image retrieval setup.

关键词： Content-based image Retrieval Bag-of-Words Spatial Context of local Features CNN features 2D index

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