Monochromatic Visualization of Multiple Images by Nonlinear Projection Pursuit.

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

Classification and Multiple Regression through Projection Pursuit*

Projection pursuit regression is generalized to multivariate responses. By viewing classification as a special case, this generalization serves to extend classification and discriminant analysis via the projection pursuit approach. Submitted to Journal of the American Statistical Association * Work supported by the Department of Energy under contract DEAC03-76SF00515, by the Office of Naval Res...

متن کامل

Endmember Generation by Projection Pursuit

Projection pursuit (PP) is an interesting concept, which has been found in many applications. It uses a so-called projection index (PI) as a criterion to seek directions that may lead to interesting findings for data analysts. Unlike the principal components analysis (PCA), which uses variance as a measure to find directions that maximizes data variances, the PI used by the PP finds interesting...

متن کامل

Projection Pursuit and Lowpass Filtering for Preprocessing of Hypespectral Images

Hyperspectral data potentially contain more information than multispectral data because of their higher spectral resolution. However, the stochastic data analysis approaches, successfully applied to classification of multispectral data, are not as effective as those for hyperspectral data. Various investigations indicate that the key problem causing poor performance in the stochastic approaches...

متن کامل

Unsupervised target detection in hyperspectral images using projection pursuit

In this paper, we present a projection pursuit (PP) approach to target detection. Unlike most of developed target detection algorithms that require statistical models such as linear mixture, the proposed PP is to project a high dimensional data set into a low dimensional data space while retaining desired information of interest. It utilizes a projection index to explore projections of interest...

متن کامل

Nonlinear Principal Component Analysis, Manifolds and Projection Pursuit

Auto-associative models have been introduced as a new tool for building nonlinear Principal component analysis (PCA) methods. Such models rely on successive approximations of a dataset by manifolds of increasing dimensions. In this chapter, we propose a precise theoretical comparison between PCA and autoassociative models. We also highlight the links between auto-associative models, projection ...

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: The Journal of the Institute of Image Information and Television Engineers

سال: 1997

ISSN: 1881-6908,1342-6907

DOI: 10.3169/itej.51.1777