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International symposium on Intelligent signal processing and Communication Systems (ISPACS)

作者： Ming, Timothy Kwan Joon Onn, Leong Chen Zilany, Muhammad S. A. Univ Malaya Fac Engn Dept Biomed Engn Kuala Lumpur Malaysia

ISBN: (纸本)9781479961207

Comodulation masking release (CMR) is the effect of enhanced signal detection in the presence of maskers with coherent temporal fluctuations of frequency components. To gain insight into the physiological mechanism of CMR, this study employs a computational model of the auditory nerve to simulate neural responses using a band-widening paradigm at 2 kHz. signal detection theory was used to relate the population neural responses to an estimated psychophysical detection performance. The estimated thresholds of detection corresponded well with behavioral studies. A CMR of 11 dB was obtained from the simulation compared to 8-14 dB reported in behavioral studies. The result suggests that the influence on CMR at the level of the auditory nerve for increasing bandwidth is significant.

关键词： Auditory Nerve Model Comodulation Masking Release Band-Widening Experiment signal Detection Theory

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A Multiband Structure based on Hammerstein Model for Nonlinear Audio System Identification 11

A Multiband Structure based on Hammerstein Model for Nonline...

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11th International symposium on image and signal processing and Analysis (ISPA)

作者： Terenzi, A. Bruschi, V. Cornell, S. Castellani, A. Cecchi, S. Univ Politecn Marche Dept Informat Engn Ancona Italy

ISBN: (纸本)9781728131405

In recent years, the increasing computational power has enabled the large-scale use of techniques for modeling real world systems and their non-linear characteristics. Hammerstein model is a well known structure for non-linear identification of memoryless systems. The proposed work aims at showing two innovative approaches based on multiband structure adaptive filters for Hammerstein adaptive identification process. In particular two multiband structures have been developed using the discrete cosine transform and the wavelet transform for the filterbank construction. The proposed approaches have been compared with a fullband normalized least mean square (NLMS) Hammerstein model, taking into consideration synthetic and real world audio devices.

关键词： Discrete wavelet transforms Discrete cosine transforms Distortion Mathematical model computational modeling

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Unsupervised Multiobjective Design for Weighted Median Filters Using Genetic Algorithm

Unsupervised Multiobjective Design for Weighted Median Filte...

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ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： Hanada, Yoshiko Orito, Yukiko Kansai Univ Fac Engn Sci Osaka 5648680 Japan Hiroshima Univ Grad Sch Social Sci Hiroshima Japan

ISBN: (纸本)9781479945030

In this paper, a new unsupervised design method of the weighted median filter (WMF) is proposed for recovering images from impulse noise. A design problem of WMFs is to determine a suitable window shape, and an appropriate weight for each element in the window. The purpose of the filter for the noise removal is generally to estimate the original values precisely for corrupted pixels while preserving the original values of non-corrupted pixels. WMF is required to output the image with higher preservation quality and higher restoration quality, however, these qualities often have a trade-off relation. Here, we formulate the design of WMF as a multi-objective optimization problem that treats the preservation performance and the restoration performance as trade-off functions. Through the experiments, we show our method obtains a wide variety of filters that have the high preservation performance or the high restoration performance at one search process. In addition, we also discuss how to select a good set of sophisticated filters from the designed filters.

关键词： genetic algorithms image filtering image restoration impulse noise WMF corrupted pixels genetic algorithm multiobjective optimization preservation quality restoration quality unsupervised multiobjective design weighted median filters window shape Genetic algorithms image restoration Linear programming Noise Optimization Shape Genetic Algorithm (GA) Impulse noise image restoration technique median filters image filtering linear programming Filters Noise

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OPTIMAL DECOMPOSITION OF CONVEX MORPHOLOGICAL STRUCTURING ELEMENTS FOR 4-CONNECTED PARALLEL ARRAY PROCESSORS

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ieee TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE intelligence 1994年第3期16卷 304-313页

作者： PARK, H CHIN, RT UNIV WISCONSIN DEPT ELECT & COMP ENGNMADISONWI 53706

A morphological operation using a large structuring element can be decomposed equivalently into a sequence of recursive operations, each using a smaller structuring element. However, an optimal decomposition of arbitrarily shaped structuring elements is yet to be found. In this paper, we have derived an optimal decomposition of a specific class of structuring elements-convex sets-for a specific type of machine-4-connected parallel array processors. The cost of morphological operation on 4-connected parallel array processors is the total number of 4-connected shifts required by the set of structuring elements. First, the original structuring element is decomposed into a set of prime factors, and then their locations are determined while minimizing the cost function. Proofs are presented to show the optimality of the decomposition. Examples of optimal decomposition are given and compared to an existing decomposition reported by Xu.

关键词： Morphological operations image analysis image processing computational efficiency Cost function Morphology Object recognition image edge detection Shape image coding INSPEC: Controlled Indexing array signal processing image reconstruction mathematical morphology optimisation parallel processing INSPEC: Non-Controlled Indexing cost function minimization optimal decomposition convex morphological structuring elements 4-connected parallel array processors recursive operation sequence

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Unsupervised Learning of Spatial Transformations in the Absence of Temporal Continuity

Unsupervised Learning of Spatial Transformations in the Abse...

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ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： Banerjee, Bonny Dizaji, Kamran Ghasedi Univ Memphis Inst Intelligent Syst Memphis TN 38152 USA Univ Memphis Dept Elect & Comp Engn Memphis TN 38152 USA

ISBN: (纸本)9781479945030

Learning features invariant to arbitrary transformations in the data is a requirement for any recognition system, biological or artificial. Such transformations may be learned using label information or from temporal data in an unsupervised manner by exploiting continuity. This paper presents a dynamical system for learning invariances from real-world spatial patterns in an unsupervised manner and in the absence of temporal continuity. The model consists of a simple and a complex layers. Given an input, the simple layer imagines all of its variations, each with a degree of consistency, and eventually settles for the most consistent reconstruction. During this imagination, the complex layer learns the consistent variations of the same pattern as a transformation in each spatial region. Experimental results are comparable to those from supervised learning. The conditions for stability of the system are analyzed.

关键词： unsupervised learning complex layer dynamical system learning invariances real-world spatial patterns simple layer spatial transformations Computer architecture Feedforward neural networks image reconstruction Neurons Noise measurement Silicon Stability analysis Unsupervised learning DYNAMICAL SYSTEMS feedforward neural nets Noise measurement Computer Architecture image reconstruction Stability analysis Silicon Neurons

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Sequential Subspace Estimator for biometric authentication

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NEUROCOMPUTING 2015年 148卷 294-309页

作者： Malek, Obaidul Venetsanopoulos, Anastasios Androutsos, Dimitrios Zhao, Lian Ryerson Univ Toronto ON Canada

The principal challenge in biometric authentication is to mitigate the effects of any interference while extracting the biometric features for biometric template generation. Most biometric systems are developed under the assumption that extracted biometrics and the nature of their associated interferences are linear, stationary, and homogeneous. The performance of biometric authentication deteriorates when the underlying assumptions are violated due to nonlinear, nonstationary, and heterogeneous noise. Therefore, a more sophisticated filtering method needs to be developed to deal with these challenges. In this paper, a new Sequential Subspace Estimator (SSE) algorithm for biometric authentication is proposed. In the proposed method, a sequential estimator is being designed in the image subspace which addresses the challenges due to nonlinear, nonstationary, and heterogeneous noise. Furthermore, the proposed method includes a subspace technique that overcomes the computational complexity associated with the sequential estimator. The theoretical foundation of the proposed method along with the experimental results is also presented in this paper. For the experimental evaluation of the proposed method, we use facial images from two public databases: the "Put Face Database" and the "Indian Face Database". The experimental results demonstrate the superiority of the proposed method in comparison with its counterparts. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Biometric authentication image subspace Kalman filter PCA Sequential estimator

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Improvement of Recovery in Segmentation-Based Parallel Compressive Sensing

Improvement of Recovery in Segmentation-Based Parallel Compr...

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ieee International symposium on signal processing and Information Technology (ISSPIT)

作者： Mitra, Dipayan Zanddizari, Hadi Rajan, Sreeraman Carleton Univ Dept Syst & Comp Engn Ottawa ON Canada Univ S Florida Dept Elect Engn Tampa FL USA

ISBN: (纸本)9781538675687

This paper extends the recently introduced 1-D Kronecker-based Compressive Sensing (CS) recovery technique to 2-D signals and images. Traditionally large sensing matrices are used while compressing images using CS. CS when applied to individual columns of the image instead of the entire image during the sensing phase, leads to smaller sensing matrices and reduction in computational complexity. For achieving further reduction in computational complexity, the column vectors are further segmented into smaller length segments and CS is applied to each of the smaller length segments. This segmentation process reduces quality of the recovered signal. To enhance the quality of the recovered signal, the entire column vector is recovered using the Kronecker-based CS recovery technique. Magnetic Resonance (MR) images from NCIGT database were used to demonstrate the superiority of the Kronecker-based recovery for 2-D images. Structural similarity and reconstruction error were used to compare the results obtained from Kronecker-based recovery technique with non-Kronecker-based repeated recovery applied to each segments individually. Kronecker-based recovery showed improvement over non-Kronecker-based individual recovery even at higher CR.

关键词： Compressive Sensing image processing Kronecker Product signal Recovery 2-D signal processing

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Fuzzy C-Means Clustering with Spatially Weighted Information for Medical image Segmentation

Fuzzy C-Means Clustering with Spatially Weighted Information...

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ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： Kang, Myeongsu Kim, Jong-Myon Univ Ulsan Dept Elect Elect & Comp Engn Ulsan South Korea Univ Ulsan Dept IT Convergence Ulsan South Korea

ISBN: (纸本)9781479945030

image segmentation is an essential process in image analysis and is mainly used for automatic object recognition. Fuzzy c-means (FCM) is one of the most common methodologies used in clustering analysis for image segmentation. FCM clustering measures the common Euclidean distance between samples based on the assumption that each feature has equal importance. However, in most real-world problems, features are not considered equally important. To overcome this issue, we present a fuzzy c-means algorithm with spatially weighted information (FCM-SWI) that takes into account the influence of neighboring pixels on the center pixel by assigning weights to the neighbors. These weights are determined based on the distance between a corresponding pixel and the center pixel to indicate the importance of the memberships. Such a process leads to improved clustering performance. Experimental results show that the proposed FCM-SWI outperforms other FCM algorithms (FCM, modified FCM, and spatial FCM, FCM with spatial information, fast generation FCM) in both compactness and separation. Furthermore, the proposed FCM-SWI outperforms the classical algorithms in terms of quantitative comparison scores corresponding to a T1-weighted MR phantom for gray matter, white matter, and cerebrospinal fluid (CSF) slice regions.

关键词： fuzzy c-means image segmentation cluster validity function ground truth verification

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Planetary image live stacking via phase correlation 9

Planetary image live stacking via phase correlation

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9th International symposium on computational intelligence and Design (ISCID)

作者： Zhou, Haiyang Yu, Yunzhi Zhejiang Univ Coll Opt Sci & Engn Hangzhou Zhejiang Peoples R China Univ Southern Calif Dept Comp Sci Los Angeles CA USA

ISBN: (纸本)9781509035588

During planetary imaging, the complicated imaging environment, atmospheric turbulence and the equatorial mount's inaccurate compensation for the Earth's rotation will cause image degradations including noise and deformation. A low-cost solution is image stacking which stacks low exposure frames to achieve long exposure result or averages long exposure frames to reduce noise level. The most critical part of live stacking is image registration, which could effectively correct deformations among frames. There are already some offline stacking algorithms and products. However, in order to obtain better astrophotography experience, live stacking is a better choice. Astronomical live stacking emerged in deep-sky imaging fields where feature-based image registration method is preferred. However, in planetary image registration, feature-based methods may fail because of that features cannot be extracted stably and repeatedly among different images. This mainly is because of that planetary images lack enough texture features to be extracted. Therefore, area-based registration is the better choice. In this work, we proposed an algorithm based on phase correlation to implement planetary image live stacking. Benefiting from fast Fourier transformation, phase correlation has received widely applications in remote sensing, biological and medical imaging, etc. However, with the increase of image resolution, the computation cost increases too. That limits its application in real-time processing tasks. In this work, we utilized the phenomenon that the signal power of down-sampled images always concentrates in a few coherent peaks and extended the original closed-form solution to implement high resolution image live stacking with subpixel accuracy. Experiments on planetary video stream illustrates that the proposed algorithm has satisfactory results with lower computation cost compared with the original phase correlation.

关键词： phase correlation live stacking subpixel image registration planetary imaging

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The Improved Winner Filter image Restoration Based on Partition

The Improved Winner Filter Image Restoration Based on Partit...

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6th International symposium on computational intelligence and Design (ISCID)

作者： Wei, Zhiqiang Duan, Caiyan Jiang, Shuming Zhang, Yuanyuan Zhang, Jianfeng Zhu, Lianpeng Shandong Acad Sci Informat Res Inst Jinan Peoples R China Shandong Luguang Connunicat Engn CO LTD R&D Ctr Jinan Peoples R China

ISBN: (纸本)9780769550794

image restoration is a key research field in the digital image processing technology. Due to camera defocus, the relative movement and noise, the image quality declines. Because of the limitations of Wiener filtering method, the paper proposes a kind of improved Wiener filtering restoration method based on the partition. The method can not only enhance the edges and eliminate the noise, but also eliminate pseudo morph well. The PSNR of improved restoration method is higher than the original method.

关键词： image restoration Motion blurred Defocus blurred Winner filter

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