Signal Image and Video Processing

Publisher: Springer Verlag

Current impact factor: 1.43

Impact Factor Rankings

2016 Impact Factor Available summer 2017
2014 / 2015 Impact Factor 1.43
2013 Impact Factor 1.019
2012 Impact Factor 0.409
2011 Impact Factor 0.56
2010 Impact Factor 0.617

Impact factor over time

Impact factor
Year

Additional details

5-year impact 1.34
Cited half-life 2.70
Immediacy index 0.23
Eigenfactor 0.00
Article influence 0.29
Other titles Signal, image and video processing (Online), SIViP
ISSN 1863-1703
OCLC 130401260
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Springer Verlag

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    • Articles in some journals can be made Open Access on payment of additional charge
  • Classification
    green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: A new normalized subband adaptive filter based on the minimum error entropy criterion (MEE-NSAF) is proposed for identifying a highly noisy system. The MEE-NSAF utilizes a kernel function and a number of past errors in adaptation, whereas the classical NSAF relies only on the current error signal. Moreover, the stability of the MEE-NSAF is analyzed. To further improve the performance of the MEE-NSAF under the sparse impulse responses, an improved proportionate MEE-NSAF (MEE-IPNSAF) algorithm is proposed. Simulation results show that the proposed algorithms can achieve improved performance as compared with the conventional NSAF when noise gets severe.
    No preview · Article · Feb 2016 · Signal Image and Video Processing
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    ABSTRACT: In this article, we have proposed an image segmentation algorithm FABC, which is a kind of unsupervised classification (clustering), where we combine the concept of artificial bee colony optimization (ABC) and the popular fuzzy C means (FCM) and named it as fuzzy-based ABC or FABC. In FABC, we have used fuzzy membership function to search for optimum cluster centers using ABC. FABC is more efficient than other optimization techniques such as genetic algorithm (GA), particle swarm optimization (PSO) and expectation maximization (EM) algorithms. FABC overcomes the drawbacks of FCM as it does not depend on the choice of initial cluster centers and it performs better in terms of convergency, time complexity, robustness and segmentation accuracy. FABC becomes more efficient as it takes the advantage of the randomized characteristics of ABC for the initialization of the cluster centers. The experiments with FABC, GA, PSO and EM have been done over various grayscale images including some synthetic, medical and texture images, and segmentation of such images is very difficult due to the low contrast, noise and other imaging ambiguities. The efficiency of FABC is proven by both quantitative and qualitative measures.
    No preview · Article · Feb 2016 · Signal Image and Video Processing
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    ABSTRACT: This work proposes a novel methodology to describe the low-frequency behaviour of compressed 3D video streams, i.e., their average fluctuations on longer timescales. This study is innovative for two reasons. First, it proves that the low-frequency behaviour of the video data belongs to the class of quasiperiodic processes. Second, it proposes an innovative approach to describe the long-term behaviour through a set of parameters directly derived from the quasiperiodic analysis. Reported results show that the proposed approach is effective in a wide variety of simulation scenarios. Furthermore, it can be easily generalized to other kinds of compressed two-dimensional (2D) streams, whatever be the adopted algorithm, the compression degree, video resolution and format. This opens new unexplored possibilities in the field of 3D video characterization, identification and classification.
    No preview · Article · Feb 2016 · Signal Image and Video Processing
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    ABSTRACT: This paper presents an efficient compression algorithm for animated three-dimensional (3D) meshes. First, a segmentation approach is applied to achieve the motion estimation. The main idea is to exploit the temporal coherence of the geometry component by using the heat diffusion properties. The motion of the resulting regions is accurately described by 3D affine transforms. These transforms are computed at the first frame to match the subsequent ones. Second, in order to achieve a good compression performance, an efficient rate control mechanism is proposed to quantize the temporal prediction errors. At this stage, a rate-distortion model is used for quantizing the residual information. Comparative coding tests, for irregular 3D mesh sequences, were conducted to evaluate the coding efficiency of the proposed compression scheme. Simulation results show very promising performances.
    No preview · Article · Jan 2016 · Signal Image and Video Processing
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    ABSTRACT: During lifetime, teeth are exposed to many effects like abrasion, loss and dental treatments. These effects along with natural shapes of teeth form a unique dental frame which contains useful attributes to be used for human identification. Today, there exist automated dental identification systems which are used by forensics of law departments. These systems need to extract dental structures like teeth or roots prior to further analysis. So far, in several studies, much effort has been paid for this task. However, there still exist core problems like automated detection of region of interest (ROI) and segmentation in panoramic dental radiographs with missing teeth. This study aims to present a tool that can be employed to overcome these issues. Unlike previous works, the proposed methodology takes advantage of discrete wavelet transform for more accurate localization of ROI and polynomial regression to form a smooth border, separating upper and lower jaws even in case of absent teeth. Results indicate that the proposed approach can be effectively used for teeth segmentation and root apex detection.
    No preview · Article · Jan 2016 · Signal Image and Video Processing
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    ABSTRACT: Although image inpainting has been extensively studied in recent years, some problems in this area are still open. In particular, the structure restoration is one of the difficulties due to the incompleteness of the reconstructed structural information. The less reasonable filling order and the ignorance of local consistency of the image would also easily lead to undesired repairing results. To remedy the above problems, this paper proposed a new domain-based structural-aware image inpainting method. We specially designed a new iterative structure searching algorithm which can restore more complete and reliable structural information. The adjacent patches were connected to form a repairing domain which serves as the minimal repair unit. The introduction of the domain ensures the coherency and searching accuracy of the repairing results. Moreover, we introduced a novel repair order calculation method which can greatly reduce the influence of the error propagation in conventional methods. Various experiment results demonstrated the effectiveness of our method.
    No preview · Article · Jan 2016 · Signal Image and Video Processing
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    ABSTRACT: This paper proposes a new intra-mode decision method for HEVC. The proposed method makes use of the characteristics of some special modes that belong to both rough mode decision mode set and most probable mode set. It also improves the coding efficiency by adaptively applying different algorithms depending on the prediction unit size. Not only the luma components but also the chroma components are considered in this paper. In the intra-coding process for the chroma components, the proposed method changes the examination order and makes efficient use of the spatial correlation and coded block flag information. As a result, the proposed method shows significantly better performance compared to other intra-mode decision methods.
    No preview · Article · Jan 2016 · Signal Image and Video Processing
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    ABSTRACT: A novel approach to finite-impulse response system identification is given. The method is formulated differently from ordinary least mean squares (LMS) or block LMS, which are traditional approaches and has a significant advantage of speed improvement when the correlation matrix has a large condition number. Unlike other approaches which are numerically complex, this method has a similar computational burden as LMS and gives the same optimal solution after convergence. It avoids transformation matrices by writing the system description in terms of a convolution matrix which has a special lower-triangular format. In this way the correlation matrix is different from conventional least-squares approaches and maintains a modest condition number as the correlation matrix in ordinary least-squares climbs high. The method has as wide a range of applications as ordinary LMS-based solutions but can also work on deterministic inputs.
    No preview · Article · Dec 2015 · Signal Image and Video Processing
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    ABSTRACT: Low-bandwidth transmission of synthetic digital content to the end user device in the form of a scene of 3-D meshes requires efficient compression of the mesh geometry. For applications in which the meshes are observed from a single viewpoint, this work explores the use of the image rendering-based distortion measures in rate allocation to their surface regions for view-dependent mesh geometry compression. It is experimentally demonstrated that the image rendering-based distortion measures yield far superior performance (the quality of the rendered image of the reconstructed scene from a viewpoint at a given rate) in optimal rate allocation than other previously proposed distortion measures. A fast rate allocation method is also proposed for use with the image rendering-based measures for real-time or interactive applications. Not only does this method have significantly lower complexity than the optimal rate allocation method due to the rendering of the images of the reconstructed meshes at only judiciously selected rate–distortion operating points, but also its coding performance is just as competitive. Further complexity reduction in rate allocation, through rendering of only the coded regions of the meshes, is also investigated.
    No preview · Article · Dec 2015 · Signal Image and Video Processing
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    ABSTRACT: Feature extraction is one of the most important steps in processing endoscopic data. The extracted features should be invariant to image scale and rotation to provide a robust matching across a substantial range of affine distortions and changes in 3D space. In this study, a method is proposed on the basis of the dual-tree complex wavelet transform. First, a map is estimated for each scale, and then a Gaussian weighted additive function (GWAF) is determined. Keypoints are selected from local peaks of GWAF. The matching and registration are performed by applying normalized mutual information and our modified iterative closest point. Results are reported in terms of robustness to rotation, noise, color, brightness, number of keypoints, index of matching and execution time for the building, standard clinical and phantom sinus datasets. Although the results are comparable to that of the speeded up robust features, scale invariant feature transform, and the Harris method, they are more robust to the variations in rotation, brightness, color, and noise than those obtained from other methods. Registration errors obtained for consequent frames for building, clinical and phantom datasets are 0.97, 1.46 and 1.1 mm, respectively.
    No preview · Article · Dec 2015 · Signal Image and Video Processing
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    ABSTRACT: Our objective is to introduce a novel method of performing non-stationary signal analysis by means of enhanced training performance, suitable learning, and proper training dictionary elements in sparse representation techniques for real biomedical signal applications. Non-stationary signal characteristics pose severe challenges in terms of analysis and extraction of discriminant features. In addition, due to complexity of biomedical signals, the need for feature extraction algorithms that can localize to events of interest increases. To fulfil this objectives, we propose to use dictionary learning algorithms based on non-negative matrix factorization. This allows us to train the dictionary elements that lead to more robust classification performances. The proposed algorithm uses a time-frequency decomposition based on wavelet transform for non-stationary 1D biomedical signals. In this manuscript we aim to exploit non-stationary signal analysis through dictionary learning and study the discriminant features of these signals by means of sparse representation to design a robust algorithm in addition to higher classification performance.
    No preview · Article · Dec 2015 · Signal Image and Video Processing
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    ABSTRACT: Although the expected patch log likelihood (EPLL) achieves good performance for denoising, an inherent nonadaptive problem exists. To solve this problem, an adaptive learning is introduced into the EPLL in this paper. Inspired from the structured sparse dictionary, an adaptive Gaussian mixture model (GMM) is proposed based on patch priors. The maximum a posteriori estimation is employed to cluster and update the image patches. Also, the new image patches are used to update the GMM. We perform these two steps alternately until the desired denoised results are achieved. Experimental results show that the proposed denoising method outperforms the existing image denoising algorithms.
    No preview · Article · Dec 2015 · Signal Image and Video Processing
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    ABSTRACT: Achieving high-performance coding for a depth map is one of the most important challenges in 3D video coding. In this paper, a quality enhancement method is proposed to accomplish better coding efficiency. A new technique separating contour and flat regions is designed, and a contour-aware quality enhancement algorithm is presented to improve depth map quality. We also propose a fast mode decision process to reduce computational complexity. The proposed fast algorithm uses similarity between texture video and depth map coding. The encoding process for a depth map is terminated early by using coded information from a texture video. Experimental results show that the quality of the depth map is improved by 0.11–0.59 dB, which translates into a bit rate saving of 2.19–8.19 %. The proposed fast algorithm saves encoding time, on average, by 36.4 %.
    No preview · Article · Dec 2015 · Signal Image and Video Processing
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    ABSTRACT: A recursive Bayesian beamforming is proposed for the steering vector uncertainty and strong interferences. Signal and noise powers are unknown, and beamforming weight is modeled as a complex Gaussian vector that characterizes the level of projected steering vector uncertainty. By applying the Bayesian model, a recursive algorithm is developed to estimate beamforming weight. Numerical simulations of linear and planar arrays demonstrate the effectiveness and robustness of the proposed beamforming algorithm. After convergence, the proposed algorithm exhibits a performance similar to that of the optimal (Formula presented.) beamformer.
    No preview · Article · Dec 2015 · Signal Image and Video Processing
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    ABSTRACT: Multi-view video plus depth (MVD) format is considered as the next-generation standard for advanced 3D video systems. MVD consists of multiple color videos with a depth value associated with each texture pixel. Relying on this representation and by using depth-image-based rendering techniques, new viewpoints for multi-view video applications can be generated. However, since MVD is captured from different viewing angles with different cameras, significant illumination and color differences can be observed between views. These color mismatches degrade the performance of view rendering algorithms by introducing visible artifacts leading to a reduced view synthesis quality. To cope with this issue, we propose an effective method for correcting color inconsistencies in MVD. Firstly, to avoid occlusion problems and allow performing correction in the most accurate way, we consider only the overlapping region when calculating the color mapping function. These common regions are determined using a reliable feature matching technique. Also, to maintain the temporal coherence, correction is applied on a temporal sliding window. Experimental results show that the proposed method reduces the color difference between views and improves view rendering process providing high-quality results.
    No preview · Article · Dec 2015 · Signal Image and Video Processing