Automatic ports detection and recognition based on multi-features from satellite imagery

Hongchao Ma; Yun Yang

doi:10.1117/12.655265

3 November 2005 Automatic ports detection and recognition based on multi-features from satellite imagery

Hongchao Ma, Yun Yang

Proceedings Volume 6044, MIPPR 2005: Image Analysis Techniques; 60441W (2005) https://doi.org/10.1117/12.655265
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China

Abstract

This paper presents a method for ports detection based on the framework of feature level fusion. Bearing in mind the fact that parallel lines and rectangular corners are main features in most ports, and ports are large scale man-made objects, these features are firstly extracted from high-to-moderate resolution optical satellite imagery. Taking account for the balance of data acquisition and spatial resolution, SPOT panchromatic image is used for such feature extraction. Considering the whether conditions in coastal area, which is characterized by rainy and cloudy climate, Radarsat image with the similar spatial resolution as SPOT panchromatic is used to extract linear features along coastal line. Since ships and boats are typical objects that can be easily detected in radar image, these are considered to be supplemented features for ports detection. All extracted features are associated under the framework of feature level fusion. The whole procedure can be described as follows: the first step is preprocessing the input images, mainly histogram stretching to SPOT image for visual quality improvement and filtering to radar image for denoising speckles. Then registration between SPOT and Radarsat image is carried out. Since Radarsat image is used mainly for coastal line extraction and ship detection, rigorous geometric processing is omitted since little attention will be paid to land area. Common polynomial model is used for co-registration with Ground Control Points manually selected from both images. Due to feature level fusion method is adopted, registration accuracy is not as a key factor as in pixel level fusion. The next step will be linear features and rectangular corners detection both in optical and radar image. The detected linear features are then fitted by least mean-square-error algorithm. All the detected features are associated by simply weighted mean algorithm, with different weights to features from optical and radar images. An automatic ports detection system based on the abovementioned procedure is developed. Experiments show that most ports can be detected by our method.

Citation Download Citation

Hongchao Ma and Yun Yang "Automatic ports detection and recognition based on multi-features from satellite imagery", Proc. SPIE 6044, MIPPR 2005: Image Analysis Techniques, 60441W (3 November 2005); https://doi.org/10.1117/12.655265

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available