Multilevel Local Pattern Histogram for SAR Image Classification

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

Optimum Ensemble Classification for Fully Polarimetric SAR Data Using Global-Local Classification Approach

In this paper, a proposed ensemble classification for fully polarimetric synthetic aperture radar (PolSAR) data using a global-local classification approach is presented. In the first step, to perform the global classification, the training feature space is divided into a specified number of clusters. In the next step to carry out the local classification over each of these clusters, which cont...

متن کامل

Steganalysis Method for LSB Replacement Based on Local Gradient of Image Histogram

In this paper we present a new accurate steganalysis method for the LSBreplacement steganography. The suggested method is based on the changes that occur in thehistogram of an image after the embedding of data. Every pair of neighboring bins of ahistogram are either inter-related or unrelated depending on whether embedding of a bit ofdata in the image could affect both bins or not. We show that...

متن کامل

Local Quantization Code histogram for texture classification

In this paper, an efficient local operator, namely the Local Quantization Code (LQC), is proposed for texture classification. The conventional local binary pattern can be regarded as a special local quantization method with two levels, 0 and 1. Some variants of the LBP demonstrate that increasing the local quantization level can enhance the local discriminative capability. Hence, we present a s...

متن کامل

Histogram intersection kernel for image classification

In this paper we address the problem of classifying images, by exploiting global features that describe color and illumination properties, and by using the statistical learning paradigm. The contribution of this paper is twofold. First, we show that histogram intersection has the required mathematical properties to be used as a kernel function for Support Vector Machines (SVMs). Second, we give...

متن کامل

SVMs for Histogram-Based Image Classification

Traditional classification approaches generalize poorly on image classification tasks, because of the high dimensionality of the feature space. This paper shows that Support Vector Machines (SVM) can generalize well on difficult image classification problems where the only features are high dimensional histograms. Heavy-tailed RBF kernels of the form K(x,y) = e−ρ P i |x i −y i | with a ≤ 1 and ...

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: 2011

ISSN: 1545-598X,1558-0571

DOI: 10.1109/lgrs.2010.2058997