Road Detection from High Resolution Satellite Imagery Using Texture Parameters in Neural Network

نویسنده

  • M. Mokhtarzade
چکیده

In this paper, neural networks are applied on high resolution IKONOS images for road detection. It was tried to optimize neural network's functionality using a variety of texture parameters with different window sizes and gray level numbers. Both the source image and pre-classified image were used for texture parameter extraction. The obtained results were compared in terms of road and background detection accuracy. It was concluded that using texture parameters from the source image could improve road detection ability of the neural networks, while using the results of texture analysis of the pre-classified image develops the background detection accuracy.

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Object-Oriented Method for Automatic Extraction of Road from High Resolution Satellite Images

As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...

متن کامل

Automatic Road Extraction from High Resolution Satellite Images Using Neural Networks, Texture Analysis, Fuzzy Clustering and Genetic Algorithms

In this article, a new method for road extraction from high resolution Quick Bird and IKONOS pan-sharpened satellite images is presented. The proposed methodology consists of two separate stages of road detection and road vectorization. Neural networks are applied on high resolution IKONOS and Quick-Bird images for road detection. This paper has endeavoured to optimize neural networks’ function...

متن کامل

Provide a Deep Convolutional Neural Network Optimized with Morphological Filters to Map Trees in Urban Environments Using Aerial Imagery

Today, we cannot ignore the role of trees in the quality of human life, so that the earth is inconceivable for humans without the presence of trees. In addition to their natural role, urban trees are also very important in terms of visual beauty. Aerial imagery using unmanned platforms with very high spatial resolution is available today. Convolutional neural networks based deep learning method...

متن کامل

Automatic Vehicles Detection from High Resolution Satellite Imagery Using Morphological Neural Networks

This paper presents a morphological neural network approach to extract vehicle targets from high resolution panchromatic satellite imagery. In the approach, the morphological shared-weight neural network (MSNN) is used to classify image pixels on roads into vehicle targets and non-vehicle targets, and a morphology based preprocessing algorithm is developed to identify candidate vehicle pixels. ...

متن کامل

A Novel Method for Road Detection Using High Resolution Satellite Images and Lidar Data Based on One Class Svm and Lbp Features

Now a days, fast extraction of road network is a challenging task especially in urban areas where roads are covered by height objects like trees, buildings, parking lots, vehicles etc. Imagery, especially high resolution image is main source for road detection as it contains rich texture and spectral information. This paper proposes a method based on merging of features of high resolution satel...

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

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008