Title of dissertation: Dimensionality Reduction for Hyperspectral Data David P. Widemann, Doctor of Philosophy, 2008 Dissertation directed by: Professor John Benedetto Department of Mathematics Professor Wojciech Czaja Department of Mathematics This thesis is about dimensionality reduction for hyperspectral data. Special emphasis is given to dimensionality reduction techniques known as kernel e...

Abstract Blur detection is aimed to recognize the blurry pixels from a given image, which increasingly valued in vision-centered applications. Albeit great improvement achieved by recent deep learning-based methods, overweight model and rough boundary still pose challenges blur detection. In this paper, we propose Hierarchical Edge-guided Region-complemented Network (HER-Net) tackle above issue...

In blind deconvolution one aims to estimate from an input blurred image y a sharp image x and an unknown blur kernel k. Recent research shows that a key to success is to consider the overall shape of the posterior distribution p(x, k|y) and not only its mode. This leads to a distinction between MAPx,k strategies which estimate the mode pair x, k and often lead to undesired results, and MAPk str...

the image blurring is caused by motion and out of focus parameters and type of blur can be classified as global blur and local blur. In this paper the most challenging spatially varying blured detection schemes are proposed.In this the blur detection techniques for digital images are used in order to determine the blur detection several classifiers are used. In this paper we reviewed SVM & DCT ...

The fusion of imaging model and differential geometric is used to research the recognition problem of blurred-image in this paper. According to some assumptions, the established subspace results from the convolution of an image with some complete orthonormal basis functions with a predefined maximum size. Therefore, we demonstrate that the corresponding subspace created from a clear image and i...

In blind deconvolution one aims to estimate from an input blurred image y a sharp image x and an unknown blur kernel k. Recent research shows that a key to success is to consider the overall shape of the posterior distribution p(x, k|y) and not only its mode. This leads to a distinction between MAPx,k strategies which estimate the mode pair x, k and often lead to undesired results, and MAPk str...