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Blind Noisy Image Quality Assessment Using Sub-Band Kurtosis
摘要： Noise that afflicts natural images, regardless of the source, generally disturbs the perception of image quality by introducing a high-frequency random element that, when severe, can mask image content. Except at very low levels, where it may play a purpose, it is annoying. There exist significant statistical differences between distortion-free natural images and noisy images that become evident upon comparing the empirical probability distribution histograms of their discrete wavelet transform (DWT) coefficients. The DWT coefficients of low- or no-noise natural images have leptokurtic, peaky distributions with heavy tails; while noisy images tend to be platykurtic with less peaky distributions and shallower tails. The sample kurtosis is a natural measure of the peakedness and tail weight of the distributions of random variables. Here, we study the efficacy of the sample kurtosis of image wavelet coefficients as a feature driving an extreme learning machine which learns to map kurtosis values into perceptual quality scores. The model is trained and tested on five types of noisy images, including additive white Gaussian noise, additive Gaussian color noise, impulse noise, masked noise, and high-frequency noise from the LIVE, CSIQ, TID2008, and TID2013 image quality databases. The experimental results show that the trained model has better quality evaluation performance on noisy images than existing blind noise assessment models, while also outperforming general-purpose blind and full-reference image quality assessment methods.
关键词： sub-band,discrete wavelet transform (DWT),extreme learning machine (ELM),kurtosis,Blind noisy image quality assessment
更新于2025-09-23 15:23:52
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Brain MR Kurtosis Imaging Study: Contrasting Gray and White Matter
摘要： This paper mainly focuses on characterization of different brain tissues such as White and Gray matter (WM and GM) using the relation between Diffusion Tensor Imaging and Diffusion Kurtosis Imaging parameters. Both Diffusion Tensor Imaging and Diffusion Kurtosis Imaging are the extension of Diffusion Weighted Imaging, which are widely applied for analysing micro fibre structure of human organs non-invasively. Diffusion Tensor Imaging assumes that the water diffusion is in Gaussian nature and Diffusion Kurtosis Imaging accounts the deviation of the Gaussian nature. This study, conducted a correlation and regression analysis between different parametric maps generated from Diffusion Kurtosis Images. For this we have chosen 200 regions of interest pixels drawn from brain MRIs. From the results, it is observed that there is a significant variation in the correlation results between Axial Diffusion and Kurtosis Fractional Anisotropy maps of Gray matter and White matter tissues. This can be employed for enhancing accuracy in MRI segmentation techniques and also as a potential tool for Neuro degenerative disease detection.
关键词： Gray matter,Diffusion Tensor Imaging,White matter,brain MRI,Diffusion Kurtosis Imaging,Correlation analysis,Regression analysis
更新于2025-09-19 17:15:36
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Statistical sensorless short-circuit fault detection algorithm for photovoltaic arrays
摘要： One of the main challenges for the conventional protection system of a photovoltaic (PV) array is the occurrence of light fault conditions including a low location mismatch fault, a fault with a high fault path resistance, and a fault under low solar irradiance because the fault current increment is not enough for triggering current-based protective devices. The operation of the maximum power point tracking system and utilizing blocking diodes may also result in a light fault condition. An undetected fault condition causes a potential ?re hazard and energy loss. This paper proposes a waveshape based statistical fault detection algorithm for light fault detection. The proposed algorithm quanti?es the waveshape tailedness of superimposed PV array power by the kurtosis function. The proposed algorithm is able to discriminate the light fault condition from severe partial shading and is also effective for open-circuit faults. In addition to no need for additional sensors, it does not require a training dataset and prior information about the PV array. The merits of the proposed algorithm are corroborated through several case studies on a simulation model of a test PV array considering the parameter uncertainty and the presence of noise in the signals.
关键词： sensorless,photovoltaic arrays,statistical analysis,kurtosis function,fault detection
更新于2025-09-16 10:30:52
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PROPERTIES OF AIRY-GAUSS BEAMS IN THE FRACTIONAL FOURIER TRANSFORM PLANE
摘要： An analytical expression of an Airy-Gauss beam passing through a fractional Fourier transform (FRFT) system is derived. The normalized intensity distribution, phase distribution, centre of gravity, e?ective beam size, linear momentum, and kurtosis parameter of the Airy-Gauss beam are demonstrated in FRFT plane, respectively. The in?uence of the fractional order p on the normalized intensity distribution, phase distribution, centre of gravity, e?ective beam size, linear momentum, and kurtosis parameter of the Airy-Gauss beam are examined in FRFT plane. The fractional order p controls the normalized intensity distribution, phase distribution, centre of gravity, e?ective beam size, the linear momentum, and kurtosis parameter. The period of the normalized intensity, phase, and centre of gravity versus the fractional order p is 4. The period of e?ective beam size, linear momentum, and kurtosis parameter versus the fractional order p is 2. The periodic behaviors of the normalized intensity distribution, phase distribution, centre of gravity, e?ective beam size, linear momentum, and kurtosis parameter can bring novel applications such as optical switch, optical micromanipulation, and optical image processing.
关键词： phase distribution,normalized intensity distribution,kurtosis parameter,centre of gravity,effective beam size,linear momentum,Airy-Gauss beam,fractional Fourier transform
更新于2025-09-10 09:29:36
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[ASME ASME 2018 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems - San Francisco, California, USA (Monday 27 August 2018)] ASME 2018 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems - Assessment of Damage Progression in Automotive Electronics Assemblies Subjected to Temperature and Vibration
摘要： Electronics in automotive underhood environments is used for a number of safety critical functions. Reliable continued operation of electronic safety systems without catastrophic failure is important for safe operation of the vehicle. There is need for prognostication methods, which can be integrated, with on-board sensors for assessment of accrued damage and impending failure. In this paper, leadfree electronic assemblies consisting of daisy-chained parts have been subjected to high temperature vibration at 5g and 155°C. Spectrogram has been used to identify the emergence of new low frequency components with damage progression in electronic assemblies. Principal component analysis has been used to reduce the dimensionality of large data-sets and identify patterns without the loss of features that signify damage progression and impending failure. Variance of the principal components of the instantaneous frequency has been shown to exhibit an initial damage progression, increasing trend during the attaining a maximum value and decreasing prior to failure. The unique behavior of the instantaneous frequency over the period of vibration can be used as a health-monitoring feature for identifying the impending failures in automotive electronics. Further, damage progression has been studied using Empirical Mode Decomposition (EMD) technique in order to decompose the signals into Independent Mode Functions (IMF). The IMF’s were investigated based on their kurtosis values and a reconstructed strain signal was formulated with all IMF’s greater than a kurtosis value of three. PCA analysis on the reconstructed strain signal gave better patterns that can be used for prognostication of the life of the components.
关键词： high temperature vibration,prognostication,Empirical Mode Decomposition,spectrogram,kurtosis,automotive electronics,principal component analysis
更新于2025-09-09 09:28:46
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[IEEE 2018 10th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) - Beijing (2018.8.19-2018.8.20)] 2018 10th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) - A Novel Ship Segmentation Method Based on Kurtosis Test in Complex-Valued SAR Imagery
摘要： Traditional ship segmentation methods in synthetic aperture radar (SAR) imagery are mainly based on the intensity/amplitude information and cannot take fully advantage of the complex information in SAR imagery. This paper proposes a novel ship segmentation method based on kurtosis test in the complex-valued SAR imagery. It can take benefit of the complex information of the SAR imagery. The segmentation rationale is that sea clutter usually obey a Gaussian distribution while ship targets usually obey a sup-Gaussian distribution. Thus, their kurtosis can be different. Kurtosis is invariant with respect to location shift and positive scale changes. It follows that kurtosis of sea clutter remains approximately constant while the amplitude decreases with the incidence angle increasing. Preliminary experimental results based on Gaofen-3 and Sentinel-1 data show that the proposed method can achieve good performance.
关键词： synthetic aperture radar (SAR),ship segmentation,kurtosis test,Gaussianity,complex-valued
更新于2025-09-04 15:30:14