- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Blind restoration of space-variant Gaussian-like blurred images using regional PSFs
摘要： In this paper, we propose an alternative de-blurring method to remove Gaussian blurs (that approximate distortions such as out-of-focus and long atmospheric path). Our research focuses on images that contain space-variant blurs, as well as focused objects within the same image. We propose to use estimated depth map-based segmentation for space-variant blind image de-blurring. Unlike previous studies that assume PSF or use one calculated PSF for the entire image, our method composes re-blurred images using different calculated PSF’s and combining the restored images to one restored image. The proposed method contains several parts: blur map estimation based on edge-width analysis, division of the image into several layers according to the blur severity, and extraction of the point-spread function (PSF) that characterizes the blur at each layer. Next, each layer is de-blurred using its speci?c PSF and the total variation method; the de-blurred layers are combined forming the ?nal restored image. A main challenge is to prevent distortions of the sharper objects in the image while simultaneously sharpening the blurrier objects.
关键词： Blind restoration,Deblurring,Total variation,Gaussian blur
更新于2025-09-04 15:30:14
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Theoretical Insights on Nonlinear Response Theory of Fluorescence Spectroscopy in Liquids
摘要： Correlations between the nonequilibrium solvation dynamics upon the photon excitation of the chromophore and system’s equilibrium fluctuations are deeply studied. As linear response of the solvent has been linked with Gaussian statistics of the energy fluctuations in literatures, we specifically explore the cases beyond the regime of the linear response theory due to deviation from Gaussian fluctuations. As a continuation of our previous work, an analytical formalism is presented to project the energy shift with various order moments, where the non-Gaussian statistics arise from the overlap of the energy basins on the perturbed potential energy surface. It is shown that the nonequilibrium dynamics still correlate with the spontaneous regressions at equilibrium, and are controlled by the decay rates of those higher order components with the prevailing contributions to the energy shift. Molecular dynamics simulations were performed in the protein Staphylococcus nuclease, in which even the dynamics of the high order moments are available. The results further verify the above relationship. Our scheme is used to evaluate Stokes shift using the information of non-Gaussian statistics at equilibrium, thus presenting a broad picture on the correlation between the nonequilibrium process and equilibrium properties in liquids.
关键词： non-Gaussian statistics,solvation dynamics,equilibrium fluctuations,nonequilibrium dynamics,fluorescence Stokes shift
更新于2025-09-04 15:30:14
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An effective image denoising using PPCA and classification of CT images using artificial neural networks
摘要： The main aim of denoising is to remove the noise while recollecting as much possible important signal features. This appears to be very simple when considered under practical situations, where the type of images and noises are all variable parameters. This paper deals with removal of combination of noises from image and classification of normal and abnormal images. At first phase, median filter is used to remove the noises present in the images. To improve the denoised output, we are using PSM and PPCA with morphological operations, filter and region props. In the second phase, to analyse the denoised output, neural network-based classification is proposed. The use of artificial intelligent techniques for classification shows a great potential in this field. Hence the performance of neural network classifier is estimated in terms of training performance and classification accuracy and is compared with the existing method to show the system is effective.
关键词： GLCM,median filter,Gaussian noise,pixel surge model,CT images,neural networks,image denoising,PPCA
更新于2025-09-04 15:30:14