Signal Image and Video Processing

Publications in this journal

• Article: Simplification Method for Textured Polygonal Meshes based on Structural Appearance

  Carlos González, Pascual Castelló, Miguel Chover, Mateu Sbert, Miquel Feixas, Jesús Gumbau
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  ABSTRACT: This paper proposes an image-based simplification method for textured triangle meshes that preserves the structural appearance of textured models. Models used in interactive applications are usually composed of textured polygonal meshes. Since textures play an important role in the final appearance of the simplified model, great distortions can be obtained if texture information is not considered in the simplification process. Our method is based on an information channel created between a sphere of viewpoints and the texture regions. This channel enables us to define both the Shannon entropy and the mutual information associated with each viewpoint, and their respective generalizations based on Harvda–Charvát–Tsallis entropy. Several experiments show that great visual distortions are avoided when textured models are simplified using our method.
  Signal Image and Video Processing 05/2013; 7(3):479-492.
• Article: Automatic selection and fusion of color spaces for image thresholding

  Navid Razmjooy · B. Somayeh Mousavi · Mohsen Khalilpour · Hossein Hosseini
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  ABSTRACT: Automatic selection of color models has a great significance for machine vision purposes like image segmentation, object recognition, etc. Typically, selection of a proper color model is a problem that can just solve by testing the models on the target one by one. To achieve a proper color model, in this article, we propose a new method which is shaped on the basis of clustering and relation among models. The proposed method is verified experimentally for two different images (in thresholding purpose). The experimental results show that this method has a suitable power for automatic purposes.
  Signal Image and Video Processing 02/2013;
• Article: Block DCT to wavelet transcoding in transform domain

  Viswanath Kapinaiah, Jayanta Mukherjee, Prabir Kumar Biswas
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  ABSTRACT: The Discrete Cosine Transform (DCT) to wavelet transcoding provides input for several wavelet-based post-processing techniques of the DCT-coded image/video signals. Transcoding in domain transform avoids inverse transform and retransform operations and saves computation. In this paper, we propose a new technique for transcoding the DCT blocks to wavelet coefficients directly in the transform domain. We perform filtering, IDCT and downsampling operations in a single combined step. The proposed technique achieves the same computational result as that of a spatial domain technique. The transcoding matrices used in the proposed technique are found to satisfy certain symmetric and sparse properties, which are exploited to reduce the computational cost. As the number of zeros in the DCT coefficients is significantly higher compared to the spatial domain, computational cost reduces significantly. Also, with the proposed technique, it is possible to speedup the operation by ignoring some elements in the filtering matrices whose magnitudes are smaller than a threshold value. We demonstrate the application of the proposed transcoding for deblocking of the DCT-coded images in wavelet domain. KeywordsBlock DCT–DWT–Transcoding–Transform domain filtering–Deblocking
  Signal Image and Video Processing 05/2012;
• Article: Reduction of musical residual noise using perceptual tools with classic speech denoising techniques

  Anis Ben Aicha, Sofia Ben Jebara
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  ABSTRACT: Single channel enhancement techniques based on short-time spectral amplitude (STSA) estimation have the major drawback of generating an artificial and annoying residual noise with musical character, due mainly to the unwanted peaks in the denoised signal spectrum. The detection and reduction of spectral peaks which have a musical characteristic are the main objectives of this paper. The proposed perceptual technique to reduce musical residual noise operates as a post-processing. Based on human auditory properties, the perceptual post-processing is established in a number of steps. First, we detect musical peaks by comparing tonality coefficients in each critical band of both denoised signal and reference signal. Detected musical peaks are audible only if they exceed the clean speech masking threshold (MT). However, the clean MT is not available. It is estimated by modifying the Johnston model. Secondly, we reduce the musical residual noise by removing only audible musical peaks which exceed the estimated MT. The proposed method is tested and compared with classic STSA technique and perceptual techniques at various levels of white and colored noise. Results show the validity of the proposed technique. KeywordsMusical residual noise–Critical band–Tonality coefficient–Masking threshold
  Signal Image and Video Processing 05/2012; 6(1):85-97.
• Article: Semantic image classification by genetic algorithm using optimised fuzzy system based on Zernike moments

  B. Somayeh Mousavi, Fazlollah Soleymani, Navid razmjooy
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  ABSTRACT: Image classification is a challenging problem of computer vision. This study reports a fuzzy system to semantic image classification. As it is a complex task, various information of digital image, including three color space components and two Zernike moments with different order, are gathered and utilized as an input of fuzzy inference system to materialize a robust rotation/lighting condition and size invariant image classifier. For better performance, all the membership functions are optimized by genetic algorithm after empirical design stage. 90.62 and 96.25 % classification rates for RGB and HSI color spaces confirm the reliability of optimized system in different image conditions given in this contribution.
  Signal Image and Video Processing 05/2012;
• Article: Image quality assessment based on S-CIELAB model

  Lihuo He, Xinbo Gao, Wen Lu, Xuelong Li, Dacheng Tao
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  ABSTRACT: This paper proposes a new image quality assessment framework which is based on color perceptual model. By analyzing the shortages of the existing image quality assessment methods and combining the color perceptual model, the general framework of color image quality assessment based on the S-CIELAB color space is presented. The S-CIELAB color model, a spatial extension of CIELAB, has an excellent performance for mimicking the perceptual processing of human color vision. This paper incorporates excellent color perceptual characteristics model with the geometrical distortion measurement to assess the image quality. First, the reference and distorted images are transformed into S-CIELAB color perceptual space, and the transformed images are evaluated by existing metric in three color perceptual channels. The fidelity factors of three channels are weighted to obtain the image quality. Experimental results achieved on LIVE database II shows that the proposed methods are in good consistency with human subjective assessment results. KeywordsImage quality assessment–Color vision–S-CIELAB–Perceptual characteristics
  Signal Image and Video Processing 04/2012; 5(3):283-290.
• Article: Motion compensation of non-linear stepped-frequency pulse train by least step error

  Yingrui Hu, Xuegang Wang
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  ABSTRACT: Traditional stepped-frequency chirp pulse train suffers from high sidelobes and difficulty in compensating Doppler effect caused by target motion. This paper investigates a class of non-linear stepped-frequency chirp pulse train with low sidelobes and capability of clutter cancelation and motion compensation. An easy realizable least step error algorithm is developed to estimate the target’s radial velocity, which avoids multiple bursts required by other methods. The high signal-to-noise ratio as a result of sub-pulse compression assures the accuracy of estimation. The Cramer–Rao bound for lower limit on velocity estimation of the pulse train is derived to demonstrate its performance. KeywordsMotion compensation-Velocity estimation-Least step error-One-dimensional range profile-Non-linear stepped-frequency chirp pulse train
  Signal Image and Video Processing 04/2012; 4(3):331-336.
• Article: A comprehensive assessment of the structural similarity index

  Richard Dosselmann, Xue Dong Yang
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  ABSTRACT: In recent years the structural similarity index has become an accepted standard among image quality metrics. Made up of three components, this technique assesses the visual impact of changes in image luminance, contrast, and structure. Applications of the index include image enhancement, video quality monitoring, and image encoding. As its status continues to rise, however, so do questions about its performance. In this paper, it is shown, both empirically and analytically, that the index is directly related to the conventional, and often unreliable, mean squared error. In the first evaluation, the two metrics are statistically compared with one another. Then, in the second, a pair of functions that algebraically connects the two is derived. These results suggest a much closer relationship between the structural similarity index and mean squared error. KeywordsStructural similarity index–SSIM–Mean squared error–MSE–Image quality metric
  Signal Image and Video Processing 04/2012; 5(1):81-91.
• Article: B-spline wavelets for signal denoising and image compression

  M. F. Fahmy, Gamal Fahmy, O. F. Fahmy
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  ABSTRACT: In this paper we propose to develop novel techniques for signal/image decomposition, and reconstruction based on the B-spline mathematical functions. Our proposed B-spline based multiscale/resolution representation is based upon a perfect reconstruction analysis/synthesis point of view. Our proposed B-spline analysis can be utilized for different signal/imaging applications such as compression, prediction, and denoising. We also present a straightforward computationally efficient approach for B-spline basis calculations that is based upon matrix multiplication and avoids any extra generated basis. Then we propose a novel technique for enhanced B-spline based compression for different image coders by preprocessing the image prior to the decomposition stage in any image coder. This would reduce the amount of data correlation and would allow for more compression, as will be shown with our correlation metric. Extensive simulations that have been carried on the well-known SPIHT image coder with and without the proposed correlation removal methodology are presented. Finally, we utilized our proposed B-spline basis for denoising and estimation applications. Illustrative results that demonstrate the efficiency of the proposed approaches are presented. KeywordsB-splines–Wavelets–Signal denoising–Image compression
  Signal Image and Video Processing 04/2012; 5(2):141-153.
• Article: Geometric image registration under arbitrarily-shaped locally variant illuminations

  Mohamed M. Fouad, Richard M. Dansereau, Anthony D. Whitehead
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  ABSTRACT: In geometric image registration, illumination variations that exist between image pairs tend to degrade the precision of the registration, which can negatively affect subsequent processing. In this paper, we present a model to improve the sub-pixel geometric registration precision of image pairs when there exists locally variant illuminations with arbitrary shape. This model extends on our previous work to include multiple local shading levels of arbitrary shape, where the ill-posed problem is conditioned by constraining the solution to an estimated number of shading levels. The proposed model is solved using least-squares estimation and is cast in an iterative coarse-to-fine framework, which allows a convergence rate that is similar to competing intensity-based image registration approaches. The primary advantage of the proposed approach is the nearly tenfold improvement in sub-pixel precision for the registration when convergence is obtained in this class of technique. KeywordsSub-pixel geometric registration-Global and local illumination variations
  Signal Image and Video Processing 04/2012; 6(4):521-532.
• Article: Clinical decision support system for early prediction of Down syndrome fetus using sonogram images

  S. Nirmala, V. Palanisamy
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  ABSTRACT: In this paper, the segmentation and extraction of features from ultrasound second trimester fetal images have been presented for early detection of Down syndrome. The region of interest and the edges of the segmented region have been obtained using mean shift analysis and Canny operator, respectively. The prime features such as the nasal bone, the palate and the frontal bone have been segmented for estimating the nasal bone length and frontomaxillary facial angle (FMF). It is observed from the results that the rate of growth of nasal bone length is poor and the FMF angle has been found to increase above 85° for fetus with trisomy 21. This analysis may help the physician for better clinical diagnosis. KeywordsDown syndrome–Mean shift analysis–Nasal bone Length–Frontomaxillary facial angle
  Signal Image and Video Processing 04/2012; 5(2):245-255.
• Article: Automatic liver and lesion segmentation: a primary step in diagnosis of liver diseases

  S. S. Kumar, R. S. Moni, J. Rajeesh
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  ABSTRACT: Computed Tomography (CT) images are widely used for diagnosis of liver diseases and volume measurement for liver surgery and transplantation. Segmentation of liver and lesion is regarded as a major primary step in computer-aided diagnosis of liver diseases. Lesion alone cannot be segmented automatically from the abdominal CT image since there are tissues external to the liver with similar intensity to the lesions. Therefore, it is necessary to segment the liver first so that lesion can then be segmented accurately from it. In this paper, an approach for automatic and effective segmentation of liver and lesion from CT images needed for computer-aided diagnosis of liver is proposed. The method uses confidence connected region growing facilitated by preprocessing and postprocessing functions for automatic segmentation of liver and Alternative Fuzzy C-Means clustering for lesion segmentation. The algorithm is quantitatively evaluated by comparing automatic segmentation results to the manual segmentation results based on volume measurement error, figure of merit, spatial overlap, false positive error, false negative error, and visual overlap. KeywordsLiver segmentation–Lesion segmentation–Volume measurement-confidence connected region growing–Alternative FCM
  Signal Image and Video Processing 04/2012;
• Article: Semi-transparent blotches removal from sepia images exploiting visibility laws

  Vittoria Bruni, Andrew Crawford, Anil Kokaram, Domenico Vitulano
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  ABSTRACT: This paper presents a novel model for the removal of semi-transparent blotches on the digitized copy of sepia archive photographs. As these defects cannot be successfully eliminated by conventional interpolation methods, a proper combination of a novel visual distortion and multiresolution analysis is used for performing user-independent detection and restoration. Extensive experimental results and comparative studies show the potential of the proposed model in terms of visual quality and computational complexity. KeywordsImage restoration–Semi-transparent blotches–HVS–Visual contrast–Multiscale analysis
  Signal Image and Video Processing 04/2012;
• Article: Design of digital FIR variable fractional order integrator and differentiator

  Abdelfatah Charef, Tahar Bensouici
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  ABSTRACT: This paper presents an easy and simple method to design variable fractional order digital FIR integrators and differentiators based on fractional order systems. First, closed-form digital IIR fractional order integrators and differentiators have been obtained from the analog rational functions approximations, in a given frequency band, of the fractional order integrator s −m and differentiator s m (0<m<1) through the Tustin generating function. Then, closed-form digital FIR fractional order integrators and differentiators by truncation of the digital IIR ones have been derived. Next, polynomial interpolation has been used to design digital FIR variable fractional order integrators and differentiators that can be implemented by the Farrow structure. The main feature of variable fractional order operator is that its order can be changed without re-designing a new fractional order operator. Some examples have been presented through the paper to illustrate the performance and the effectiveness of the proposed design method. The results obtained have been discussed and have been compared to one of the most recent works in the literature using the same design parameters. KeywordsFractional order differentiator–Fractional order integrator–Digital IIR filters–Digital FIR filters–Farrow structure
  Signal Image and Video Processing 04/2012;
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  Article: An improved image graph for semi-automatic segmentation

  Daniel Freedman
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  ABSTRACT: The problem of semi-automatic segmentation has attracted much interest over the last few years. The Random Walker algorithm [1] has proven to be quite a popular solution to this problem, as it is able to deal with several components and models the image using a convenient graph structure. We propose two improvements to the image graph used by the Random Walker method. First, we propose a new way of computing the edge weights. Traditionally, such weights are based on the similarity between two neighbouring pixels, using their greyscale intensities or colours. We substitute a new definition of weights based on the probability distributions of colours. This definition is much more robust than traditional measures, as it allows for textured objects, and objects that are composed of multiple perceptual components. Second, the traditional graph has a vertex set which is the set of pixels and edges between each pair of neighbouring pixels. We substitute a smaller, irregular graph based on Mean Shift oversegmentation. This new graph is typically several orders of magnitude smaller than the original image graph, which can lead to a major savings in computing time. We show results demonstrating the substantial improvement achieved when using the proposed image graph. KeywordsImage segmentation-Graph-Probability distribution-Random walk
  Signal Image and Video Processing 04/2012;
• Article: A new fuzzy-based decision algorithm for high-density impulse noise removal

  Madhu S. Nair, G. Raju
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  ABSTRACT: This paper proposes a new efficient fuzzy-based decision algorithm (FBDA) for the restoration of images that are corrupted with high density of impulse noises. FBDA is a fuzzy-based switching median filter in which the filtering is applied only to corrupted pixels in the image while the uncorrupted pixels are left unchanged. The proposed algorithm computes the difference measure for each pixel based on the central pixel (corrupted pixel) in a selected window and then calculates the membership value for each pixel based on the highest difference. The algorithm then eliminates those pixels from the window with very high and very low membership values, which might represent the impulse noises. Median filter is then applied to the remaining pixels in the window to get the restored value for the current pixel position. The proposed algorithm produces excellent results compared to conventional method such as standard median filter (SMF) as well as some advanced techniques such as adaptive median filters (AMF), efficient decision-based algorithm (EDBA), improved efficient decision-based algorithm (IDBA) and boundary discriminative noise detection (BDND) switching median filter. The efficiency of the proposed algorithm is evaluated using different standard images. From experimental analysis, it has been found that FBDA produces better results in terms of both quantitative measures such as PSNR, SSIM, IEF and qualitative measures such as Image Quality Index (IQI). KeywordsFuzzy-Decision-based-Impulse noise-Median filter-Salt-and-pepper noise
  Signal Image and Video Processing 04/2012;
• Article: Direction-finding of coherent signals based on cylindrical vector-hydrophones array

  Jian-Wu Tao, Wen-Xiu Chang, Wei Cui
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  ABSTRACT: In this paper, a new “particle-velocity-field and spatial smoothing” (PVFSS) algorithm is proposed for direction-finding of coherent signals, using the cylindrical vector-hydrophones array in the underwater acoustic medium. In contrast to the customary “spatial smoothing” technique, it provides a smaller reduction in the overall array’s spatial aperture. While in contrast to the “particle-velocity-field smoothing” technique, it may increase the number of decorrelate-able coherent signals. Moreover, an ESPRIT-based, closed-form direction-finding algorithm is proposed and a method of removing cyclic ambiguity is provided. Finally, the theoretical performance of the proposed algorithm is analyzed. Simulation results are shown to verify the efficacy of the proposed algorithm. KeywordsCoherent signal-Vector-hydrophone smoothing algorithm-Direction of arrival estimation-Cylindrical arrays
  Signal Image and Video Processing 04/2012; 4(2):221-232.
• Article: A Robust hierarchical motion estimation algorithm in noisy image sequences in the bispectrum domain

  El Mehdi Ismaili Alaoui, Elhassane Ibn-Elhaj
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  ABSTRACT: The present study describes a robust hierarchical motion estimation algorithm in noisy image sequences using the bispectrum. The motion can be characterized by an affine model and the parameters of an affine motion model are estimated by means third-order auto-bispectrum and cross-bispectrum measures. The basic components of this framework to obtain motion vectors are (i) pyramid construction, (ii) motion estimation and (iii) coarse-to-fine refinement. The entire motion is decomposed as a global and a local motion field, which helps accurately obtain high resolution estimates for the local motion field. Simulation results are presented and compared to those obtained from the phase correlation algorithm. The results demonstrate that the proposed method is more suited than the phase correlation algorithm to analyses complex noisy image sequences. On the other hand, our method produces smoother displacement vector field with a more accurate measure of object motion in different signal-to-noise ratio scenarios.
  Signal Image and Video Processing 04/2012; 3(3):291-302.
• Article: A new fourth order embedded RKAHeM(4,4) method with error control on multilayer raster cellular neural network

  R. Ponalagusamy, S. Senthilkumar
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  ABSTRACT: We introduce a new technique for solving initial value problems (IVPs) with error control by formulating an embedded method involving RK methods based on arithmetic mean (AM) and Heronian mean (HeM). The function of the simulator is that it is capable of performing raster simulation for any kind as well as any size of input image. It is a powerful tool for researchers to examine the potential applications of CNN. By using the newly proposed embedded method, a versatile algorithm for simulating multilayer CNN arrays is implemented. This article proposes an efficient pseudo code for exploiting the latency properties of CNN along with well known RK-fourth order embedded numerical integration algorithms. Simulation results and comparison have also been presented to show the efficiency of the numerical integration algorithms. It is found that the RK-embedded Heronian mean outperforms well in comparison with the RK-embedded centroidal mean, harmonic mean and contra-harmonic mean. A more quantitative analysis has been carried out to clearly visualize the goodness and robustness of the proposed algorithm.
  Signal Image and Video Processing 04/2012; 3(1):1-11.