The Experts below are selected from a list of 55911 Experts worldwide ranked by ideXlab platform
Wei Wang - One of the best experts on this subject based on the ideXlab platform.
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Saturation-Value Total Variation model for chromatic aberration correction
Inverse Problems & Imaging, 2020Co-Authors: Wei WangAbstract:Chromatic aberration generally occurs in the regions of sharp edges in captured digital color images. The main aim of this paper is to propose and develop a novel Saturation-Value Total Variation (SVTV) model for chromatic aberration correction. In the proposed optimization model, there are three terms for the correction purpose. The SVTV regularization term is to model the target color image in HSV color space instead of RGB color space, and to avoid oscillations in the recovering process. In correction process, the gradient matching terms based on the green component are used to govern both red and blue components, and the intensity terms are employed to fit red, green and blue data components. The existence of the minimizer of the optimization model is analyzed and an efficient optimization algorithm is also developed for solving the resulting variational problem. Experimental results are presented to illustrate the effectiveness of the proposed model and to show that the correction results are better than those by using the other testing methods.
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Color Image Restoration by Saturation-Value Total Variation
SIAM Journal on Imaging Sciences, 2019Co-Authors: Zhigang Jia, Wei WangAbstract:Color image restoration is one of the important tasks in color image processing. Total variation regularizaton was proposed and employed for the recovery of edges in a grayscale image. In the liter...
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Color image multiplicative noise and blur removal by Saturation-Value total variation
Applied Mathematical Modelling, 1Co-Authors: Wei Wang, Mingjia YaoAbstract:Abstract In this paper, we propose and develop a novel Saturation-Value Total Variation (SVTV) model for multiplicative noise and blur removal of color images. In the proposed model, SVTV regularization term is applied to model the target color image in HSV color space instead of RGB color space, and the fidelity term is well-adapted to multiplicative noise. We investigate into the existence and uniqueness of the minimizer of the proposed minimization problem. We study and show the convergence of an implicit scheme of the associated evolution problem for the numerical solution of the proposed SVTV model. Numerical examples are presented to demonstrate the performance of the proposed SVTV model is significantly better than that of other testing methods in terms of some criteria such as PSNR, SSIM and S-CIELAB color error.
Vincent Maida - One of the best experts on this subject based on the ideXlab platform.
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Towards algorithm-enabled home wound monitoring with smartphone photography: A hue-Saturation-Value colour space thresholding technique for wound content tracking.
International wound journal, 2018Co-Authors: Runjie Bill Shi, Jimmy Qiu, Vincent MaidaAbstract:Automated tracking of wound-healing progress using images from smartphones can be useful and convenient for the patient to perform at home. To evaluate the feasibility, 119 images were taken with an iPhone smartphone during the treatment of a chronic wound at one patient's home. An image analysis algorithm was developed to quantitatively classify wound content as an index of wound healing. The core of the algorithm involves transforming the colour image into hue-Saturation-Value colour space, after which a threshold can be reliably applied to produce segmentation using the Black-Yellow-Red wound model. Morphological transforms are used to refine the classification. This method was found to be accurate and robust with respect to lighting conditions for smartphone-captured photos. The wound composition percentage showed a different trend from the wound area measurements, suggesting its role as a complementary metric. Overall, smartphone photography and automated image analysis is a promising cost-effective way of monitoring patients. While the current setup limits our capability of measuring wound area, future smartphones equipped with depth-sensing technology will enable accurate volumetric evaluation in addition to composition analysis.
Pierre Pujol - One of the best experts on this subject based on the ideXlab platform.
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MAGNETIZATION CURVES OF ANTIFERROMAGNETIC HEISENBERG SPIN-1/2 LADDERS
Physical Review Letters, 1997Co-Authors: Daniel C. Cabra, Andreas Honecker, Pierre PujolAbstract:Magnetization processes of spin-1/2 Heisenberg ladders are studied using strong-coupling expansions, numerical diagonalization of finite systems and a bosonization approach. We find that the magnetization exhibits plateaux as a function of the applied field at certain rational fractions of the Saturation Value. Our main focus are ladders with 3 legs where plateaux with magnetization one third of the Saturation Value are shown to exist.
Martin Wolf - One of the best experts on this subject based on the ideXlab platform.
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The effect of basic assumptions on the tissue oxygen Saturation Value of near infrared spectroscopy.
Advances in experimental medicine and biology, 2012Co-Authors: Andreas Jaakko Metz, Martin Biallas, Carmen Jenny, Thomas Muehlemann, Martin WolfAbstract:Tissue oxygen Saturation (StO2), a potentially important parameter in clinical practice, can be measured by near infrared spectroscopy (NIRS). Various devices use the multi-distance approach based on the diffusion approximation of the radiative transport equation [1, 2]. When determining the absorption coefficient (μa) by the slope over multiple distances a common assumption is to neglect μa in the diffusion constant, or to assume the scattering coefficient \( ({\mu }_{\text{s}}{}^{\prime })\) to be constant over the wavelength. Also the water influence can be modeled by simply subtracting a water term from the absorption. This gives five approaches A1–A5. The aim was to test how these different methods influence the StO2 Values. One data set of 30 newborn infants measured on the head and another of eight adults measured on the nondominant forearm were analyzed. The calculated average StO2 Values measured on the head were (mean ± SD): A1: 79.99 ± 4.47%, A2: 81.44 ± 4.08%, A3: 84.77 ± 4.87%, A4: 85.69 ± 4.38%, and A5: 72.85 ± 4.81%. The StO2 Values for the adult forearms are: A1: 58.14 ± 5.69%, A2: 73.85 ± 4.77%, A3: 58.99 ± 5.67%, A4: 74.21 ± 4.76%, and A5: 63.49 ± 5.11%. Our results indicate that StO2 depends strongly on the assumptions. Since StO2 is an absolute Value, comparability between different studies is reduced if the assumptions of the algorithms are not published.
Iain S. Young - One of the best experts on this subject based on the ideXlab platform.
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efficient individual identification of zebrafish using hue Saturation Value color model
The Egyptian Journal of Aquatic Research, 2018Co-Authors: Qussay Aljubouri, R J Alazawi, Majid A Altaee, Iain S. YoungAbstract:Abstract Automated fish species recognition is widely investigated in research but it is not explored for the individuals with the same fish species. A new classifying method for zebrafish individuals that is based on statistical texture and Hue/Saturation/Value (HSV) color features are presented in this paper. Post image acquisition, pre-processing stages and features of sub-images are extracted, using statistical texture and HSV color space domain, and grouped into HSV and statistical sets of features. An artificial neural network (ANN) and K-Nearest Neighbors (KNN) are then used to identify the subjects under test. The impact of using statistical and HSV features on the prediction accuracy and average processing time is then assessed experimentally. An improved performance for the HSV over the statistical model is clearly demonstrated. The combination of HSV model and KNN classifier has also demonstrated a superior performance over the combination of HSV and ANN classifier in terms of the accuracy (KNN = 99.0%; ANN = 97.8%) and average processing time (KNN = 4.1 ms; ANN = 24.2 ms). Such promising findings encourage further testing of the HSV model towards developing a highly-efficient and fully-automated identification system for small species individual like zebrafish.
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Efficient individual identification of zebrafish using Hue/Saturation/Value color model
The Egyptian Journal of Aquatic Research, 2018Co-Authors: Qussay Al-jubouri, R.j. Al-azawi, Majid A. Al-taee, Iain S. YoungAbstract:Abstract Automated fish species recognition is widely investigated in research but it is not explored for the individuals with the same fish species. A new classifying method for zebrafish individuals that is based on statistical texture and Hue/Saturation/Value (HSV) color features are presented in this paper. Post image acquisition, pre-processing stages and features of sub-images are extracted, using statistical texture and HSV color space domain, and grouped into HSV and statistical sets of features. An artificial neural network (ANN) and K-Nearest Neighbors (KNN) are then used to identify the subjects under test. The impact of using statistical and HSV features on the prediction accuracy and average processing time is then assessed experimentally. An improved performance for the HSV over the statistical model is clearly demonstrated. The combination of HSV model and KNN classifier has also demonstrated a superior performance over the combination of HSV and ANN classifier in terms of the accuracy (KNN = 99.0%; ANN = 97.8%) and average processing time (KNN = 4.1 ms; ANN = 24.2 ms). Such promising findings encourage further testing of the HSV model towards developing a highly-efficient and fully-automated identification system for small species individual like zebrafish.
