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Phylogeny of JPEG images by ancestor estimation using missing markers on image pairs 6

Phylogeny of JPEG images by ancestor estimation using missin...

引用

6th International conference on image processing Theory, Tools and applications (IPTA)

作者： Le Philippe, Noe Puech, William Fiorio, Christophe Univ Montpellier CNRS LIRMM Lab UMR 5506 Montpellier France

ISBN: (纸本)9781467389105

Nowadays it is extremely easy to tamper with images and share them thanks to social media. Identifying the transformation history is imperative to be able to trust these images. We address this problem by using image phylogeny trees, where the root is the image that has been less tampered with and as every generation is obtained from the transformation of its parents, the leaves are the most transformed images. Our method for image phylogeny trees reconstruction is based on a binary decision between two images using JPEG compression artifacts. Experimental results show that when there is no missing image data, the reconstruction is very accurate.

关键词： image phylogeny JPEG compression Social networks image phylogeny tree near-duplicates

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Structure-Based image Inpainting 6

Structure-Based Image Inpainting

引用

6th International conference on image processing Theory, Tools and applications (IPTA)

作者： Akl, Adib Saad, Edgard Yaacoub, Charles Holy Spirit Univ Kaslik USEK Fac Engn POB 446 Jounieh Lebanon

ISBN: (纸本)9781467389105

image inpainting is a dynamic field with different image processing and computer graphics applications. Most of the existing image inpainting methods lead to significant results in different applications but fail in difficult situations with high local structural variations. In this paper, a structure-based image inpainting algorithm is proposed, where the image's structure layer is represented and analyzed using the structure tensor field. The structure layer of the image is first inpainted by adapting the Efros and Leung algorithm to the specificities of the structure tensor, then the obtained tensor field is used to help the image inpainting process. Results show that using the proposed method, relevant local information can be better inpainted comparing to the initial intensity-based approach that does not consider structural information during the inpainting process.

关键词： image Inpainting Structure Layer Reference image Structure Tensor Field Local Orientation

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On Semantic image Segmentation Using Deep Convolutional Neural Network with Shortcuts and Easy Class Extension 6

On Semantic Image Segmentation Using Deep Convolutional Neur...

引用

6th International conference on image processing Theory, Tools and applications (IPTA)

作者： Wang, Chunlai Mauch, Lukas Guo, Ze Yang, Bin Univ Stuttgart Inst Signal Proc & Syst Theory Stuttgart Germany

ISBN: (纸本)9781467389105

In this paper we examine the use of deep convolutional neural networks for semantic image segmentation, which separates an input image into multiple regions corresponding to predefined object classes. We use an encoder-decoder structure and aim to improve it in convergence speed and segmentation accuracy by adding shortcuts between network layers. Besides, we investigate how to extend an already trained model to other new object classes. We propose a new strategy for class extension with only little training data and class labels. In the experiments we use two street scene datasets to demonstrate the strength of shortcuts, to study the contextual information encoded in the learned model and to show the effectiveness of our class extension method.

关键词： Semantic image segmentation Deep convolutional neural network Class extension Context

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De-Convolutional Auto-Encoder for Enhancement of Fingerprint Samples 6

De-Convolutional Auto-Encoder for Enhancement of Fingerprint...

引用

6th International conference on image processing Theory, Tools and applications (IPTA)

作者： Schuch, Patrick Schulz, Simon Busch, Christoph NTNU NISlab POB 191 N-2802 Gjovik Norway DERMALOG Identificat Syst GmbH Mittelweg 120 D-20419 Hamburg Germany

ISBN: (纸本)9781467389105

Reliability and accuracy of the features extracted from fingerprints are essential for the performance of any fingerprint comparison algorithm. image Enhancement as a pre-processing step allows to extract features more accurately by enhancing the quality of the fingerprint signal. This work proposes to use De-Convolutional Auto-Encoders for fingerprint image enhancement. Its performance is compared to seven state-of-the-art methods regarding their improvements for recognitions of the biometric system. Biometric performance is tested with MINDTCT and FingerJetFx for feature extraction and BOZORTH3 for biometric comparison. Critical comparisons are determined from 14 datasets. Those are used for evaluation of the methods. The impact of a method on biometric performance varies significantly. No single image enhancement can be found, which works best for all combinations. However, the proposed method ConvEnhance achieves highest count of best improvements among the evaluated methods.

关键词： Fingerprint Recognition image Enhancement Convolutional Neural Network Auto-Encoder

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On the Use of image Quality Measures for image Restoration 6

On the Use of Image Quality Measures for Image Restoration

引用

6th International conference on image processing Theory, Tools and applications (IPTA)

作者： Boudjenouia, Fouad Abed-Meraim, Karim Chetouani, Aladine Jennane, Rachid Univ Orleans I3MTO Lab Orleans France Univ Orleans PRISME Lab Orleans France

ISBN: (纸本)9781467389105

image quality measurements are valuable tools, crucial for most image processing applications, and used in particular to assess and compare the image restoration (IR) quality. The objective of this work is to investigate the potential of such measures when used as cost functions (integrated in the global criterion) to enhance the restoration performance. In this paper, the proposed approach uses the Structural SIMilarity (SSIM) index measure which is one of the most appropriate measures as it is inspired from the human visual system (HVS) and relatively simple to compute. For the composite criterion optimization, after initializing the algorithm by the alternating direction method of multipliers (ADMM), a gradient descent (GD) technique is used to minimize the global cost function. Finally, simulations are conducted to investigate the contexts in which such quality measures might lead to the desired IR improvement.

关键词： image restoration image quality assessment Structural similarity index measure Alternating direction method of multipliers Gradient descent

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Data Compression in Wireless Visual Sensor Networks using wavelets

Data Compression in Wireless Visual Sensor Networks using Wa...

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IEEE International conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： Sofi, Shabir Ahmad Naaz, Roohie Natl Inst Technol Srinagar Dept Informat Technol Hazratbal Kashmir India Natl Inst Technol Srinagar Dept Comp Sci & Engn Hazratbal Kashmir India

ISBN: (纸本)9781467393379

Wireless Sensor Networking is a sensor information gathering technology that has a wide range of applications in numerous fields. However due to the fact that sensor nodes have limited battery and are deployed in remote and harsh environments, energy efficient and real time transmission of the information are still open challenges. Since in a wireless sensor network data transmission is the most power consuming task, so far most useful techniques for the purpose of energy efficient and real time transmissions are based on data compression, the majority of them are based on wavelet transform. This paper give performance analysis of different wavelets for energy efficient and real time image data transmission in application like environment monitoring using wireless visual sensor networks. The performance evaluation shows that Haar wavelet is better in terms of energy efficiency and transmission time.

关键词： Wireless Visual Sensor Network (WVSN) Discrete Wavelet Transform (DWT) Skipped High-pass Sub-band (SHPS) Data Compression

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An Analysis of 3D Point Cloud Reconstruction from Light Field images 6

An Analysis of 3D Point Cloud Reconstruction from Light Fiel...

引用

6th International conference on image processing Theory, Tools and applications (IPTA)

作者： Perra, Cristian Murgia, Francesca Giusto, Daniele Univ Cagliari I-09124 Cagliari Italy

ISBN: (纸本)9781467389105

Current methodologies for the generation of 3D point cloud from real world scenes rely upon a set of 2D images capturing the scene from several points of view. Novel plenoptic cameras sample the light field crossing the main camera lens creating a light field image. The information available in a plenoptic image must be processed in order to render a view or create the depth map of the scene. This paper analyses a method for the reconstruction of 3D models. The reconstruction of the model is obtained from a single image shot. Exploiting the properties of plenoptic images, a point cloud is generated and compared with a point cloud of the same object but generated with a different plenoptic camera.

关键词： Light field coding Plenoptic coding Lossless coding image compression

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Example-based Visual Object Counting for complex background with a local low-rank constraint

Example-based Visual Object Counting for complex background ...

引用

IEEE International conference on Acoustics, Speech and signal processing

作者： x.L. Huang Y.x. Zou Y. Wang ADSPLAB/ELIP School of ECE Peking University Shenzhen 518055 China

ISBN: (纸本)9781509041183

Visual object counting (VOC) is important in many real-world applications. Our previous work approximated sparsity-constrain example-based VOC (ASE-VOC) works well with insufficient training data. It assumes that image patches share the similar local geometry with counterpart density maps, and then the density map of the image patch can be estimated by preserving such geometry. However. ASE-VOC has a weak constraint for data structure and experiments reveal that the performance of ASE-VOC degrades when facing with complex background. To solve this problem, we proposed a novel local low-rank constrained example-based VOC (LLRE-VOC) method. Because local low-rank constraint can choose the samples belonging to the subspace that lies closest to the test samples. Even with complicated data structure, LLRE-VOC can guarantee the patches selected share similar structure with input patch. Extensive experiments conducted on public benchmarks demonstrate the superior performance of our proposed LLRE-VOC method.

关键词： Visual object counting complex background local low-rank density map estimation example-based

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Hyperspectral image Analysis using Deep Learning - a Review 6

Hyperspectral Image Analysis using Deep Learning - a Review

引用

6th International conference on image processing Theory, Tools and applications (IPTA)

作者： Petersson, Henrik Gustafsson, David Bergstrom, David Swedish Def Res Agcy FOI Div C4ISR Kista Sweden

ISBN: (纸本)9781467389105

Deep learning is a rather new approach to machine learning that has achieved remarkable results in a large number of different image processing applications. Lately, application of deep learning to detect and classify spectral and spatio-spectral signatures in hyperspectral images has emerged. The high dimensionality of hyperspectral images and the limited amount of labelled training data makes deep learning an appealing approach for analysing hyperspectral data. Auto-Encoder can be used to learn a hierarchical feature representation using solely unlabelled data, the learnt representation can be combined with a logistic regression classifier to achieve results in-line with existing state-of-the-art methods. In this paper, we compare results between a set of available publications and find that deep learning perform in line with state-of-the-art on many data sets but little evidence exists that deep learning outperform the reference methods.

关键词： Hyperspectral Imaging (HSI) Deep Learning Auto-Encoder (AE) Stacked Auto-Encoder (SAE) Convolutional Neural Network (CNN) feature representation

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Single image super-resolution reconstruction in presence of mixed Poisson-Gaussian noise 6

Single image super-resolution reconstruction in presence of ...

引用

6th International conference on image processing Theory, Tools and applications (IPTA)

作者： Bajic, Buda Lindblad, Joakim Sladoje, Natasa Univ Novi Sad Fac Tech Sci Novi Sad Serbia Uppsala Univ Ctr Image Anal Dept Informat Technol Uppsala Sweden Serbian Acad Arts & Sci Math Inst Belgrade Serbia

ISBN: (纸本)9781467389105

Single image super-resolution (SR) reconstruction aims to estimate a noise-free and blur-free high resolution image from a single blurred and noisy lower resolution observation. Most existing SR reconstruction methods assume that noise in the image is white Gaussian. Noise resulting from photon counting devices, as commonly used in image acquisition, is, however, better modelled with a mixed Poisson-Gaussian distribution. In this study we propose a single image SR reconstruction method based on energy minimization for images degraded by mixed Poisson-Gaussian noise. We evaluate performance of the proposed method on synthetic images, for different levels of blur and noise, and compare it with recent methods for non-Gaussian noise. Analysis shows that the appropriate treatment of signal-dependent noise, provided by our proposed method, leads to significant improvement in reconstruction performance.

关键词： super-resolution image zooming signal dependent noise energy minimization variance stabilizing transform total variation

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