Weighted Sparse Graph Based Dimensionality Reduction for Hyperspectral Images

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Hyperspectral Dimensionality Reduction by Tensor Sparse and Low-Rank Graph-Based Discriminant Analysis

Recently, sparse and low-rank graph-based discriminant analysis (SLGDA) has yielded satisfactory results in hyperspectral image (HSI) dimensionality reduction (DR), for which sparsity and low-rankness are simultaneously imposed to capture both local and global structure of hyperspectral data. However, SLGDA fails to exploit the spatial information. To address this problem, a tensor sparse and l...

متن کامل

Impact of linear dimensionality reduction methods on the performance of anomaly detection algorithms in hyperspectral images

Anomaly Detection (AD) has recently become an important application of hyperspectral images analysis. The goal of these algorithms is to find the objects in the image scene which are anomalous in comparison to their surrounding background. One way to improve the performance and runtime of these algorithms is to use Dimensionality Reduction (DR) techniques. This paper evaluates the effect of thr...

متن کامل

Dimensionality Reduction and Classification of Hyperspectral Images using Genetic Algorithm

This paper presents genetic algorithm based band selection and classification on hyperspectral image data set. Hyperspectral remote sensors collect image data for a large number of narrow, adjacent spectral bands. Every pixel in hyperspectral image involves a continuous spectrum that is used to classify the objects with great detail and precision. In this paper, first filtering based on 2-D Emp...

متن کامل

Stability of Dimensionality Reduction Methods Applied on Artificial Hyperspectral Images

Dimensionality reduction is a big challenge in many areas. In this research we address the problem of high-dimensional hyperspectral images in which we are aiming to preserve its information quality. This paper introduces a study stability of the non parametric and unsupervised methods of projection and of bands selection used in dimensionality reduction of different noise levels determined wit...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Geoscience and Remote Sensing Letters

سال: 2016

ISSN: 1545-598X,1558-0571

DOI: 10.1109/lgrs.2016.2536658