7 resultados para SURE threshold
em Cochin University of Science
Resumo:
The standard separable two dimensional wavelet transform has achieved a great success in image denoising applications due to its sparse representation of images. However it fails to capture efficiently the anisotropic geometric structures like edges and contours in images as they intersect too many wavelet basis functions and lead to a non-sparse representation. In this paper a novel de-noising scheme based on multi directional and anisotropic wavelet transform called directionlet is presented. The image denoising in wavelet domain has been extended to the directionlet domain to make the image features to concentrate on fewer coefficients so that more effective thresholding is possible. The image is first segmented and the dominant direction of each segment is identified to make a directional map. Then according to the directional map, the directionlet transform is taken along the dominant direction of the selected segment. The decomposed images with directional energy are used for scale dependent subband adaptive optimal threshold computation based on SURE risk. This threshold is then applied to the sub-bands except the LLL subband. The threshold corrected sub-bands with the unprocessed first sub-band (LLL) are given as input to the inverse directionlet algorithm for getting the de-noised image. Experimental results show that the proposed method outperforms the standard wavelet-based denoising methods in terms of numeric and visual quality
Resumo:
A pulsed Nd-YAG laser beam is used to produce a transient refractive index gradient in air adjoining the plane surface of the sample material. This refractive index gradient is probed by a continuous He-Ne laser beam propagating parallel to the sample surface. The observed deflection signals produced by the probe beam exhibit drastic variations when the pump laser energy density crosses the damage threshold for the sample. The measurements are used to estimate the damage threshold for a few polymer samples. The present values are found to be in good agreement with those determined by other methods.
Resumo:
The acoustic signals generated in solids due to interaction with pulsed laser beam is used to determine the ablation threshold of bulk polymer samples of teflon (polytetrafluoroethylene) and nylon under the irradiation from a Q-switched Nd:YAG laser at 1.06µm wavelength. A suitably designed piezoelectric transducer is employed for the detection of photoacoustic (PA) signals generated in this process. It has been observed that an abrupt increase in the amplitude of the PA signal occurs at the ablation threshold. Also there exist distinct values for the threshold corresponding to different mechanisms operative in producing damages like surface morphology, bond breaking and melting processes at different laser energy densities.
Resumo:
Laser‐induced damage and ablation thresholds of bulk superconducting samples of Bi2(SrCa)xCu3Oy(x=2, 2.2, 2.6, 2.8, 3) and Bi1.6 (Pb)xSr2Ca2Cu3 Oy (x=0, 0.1, 0.2, 0.3, 0.4) for irradiation with a 1.06 μm beam from a Nd‐YAG laser have been determined as a function of x by the pulsed photothermal deflection technique. The threshold values of power density for ablation as well as damage are found to increase with increasing values of x in both systems while in the Pb‐doped system the threshold values decrease above a specific value of x, coinciding with the point at which the Tc also begins to fall.
Resumo:
Photothermal deflection technique was used for determining the laser damage threshold of polymer samples of teflon (PTFE) and nylon. The experiment was conducted using a Q-switched Nd-YAG laser operating at its fundamental wavelength (1-06μm, pulse width 10 nS FWHM) as irradiation source and a He-Ne laser as the probe beam, along with a position sensitive detector. The damage threshold values determined by photothermal deflection method were in good agreement with those determined by other methods.
Resumo:
In this paper we try to fit a threshold autoregressive (TAR) model to time series data of monthly coconut oil prices at Cochin market. The procedure proposed by Tsay [7] for fitting the TAR model is briefly presented. The fitted model is compared with a simple autoregressive (AR) model. The results are in favour of TAR process. Thus the monthly coconut oil prices exhibit a type of non-linearity which can be accounted for by a threshold model.
Resumo:
Biclustering is simultaneous clustering of both rows and columns of a data matrix. A measure called Mean Squared Residue (MSR) is used to simultaneously evaluate the coherence of rows and columns within a submatrix. In this paper a novel algorithm is developed for biclustering gene expression data using the newly introduced concept of MSR difference threshold. In the first step high quality bicluster seeds are generated using K-Means clustering algorithm. Then more genes and conditions (node) are added to the bicluster. Before adding a node the MSR X of the bicluster is calculated. After adding the node again the MSR Y is calculated. The added node is deleted if Y minus X is greater than MSR difference threshold or if Y is greater than MSR threshold which depends on the dataset. The MSR difference threshold is different for gene list and condition list and it depends on the dataset also. Proper values should be identified through experimentation in order to obtain biclusters of high quality. The results obtained on bench mark dataset clearly indicate that this algorithm is better than many of the existing biclustering algorithms