REMOVAL OF DIFFERENT TYPES OF NOISES IN SYNTHETIC APERTURE RADAR (SAR) IMAGES FOR IMPROVED SHIP DETECTION

Title
REMOVAL OF DIFFERENT TYPES OF NOISES IN SYNTHETIC APERTURE RADAR (SAR) IMAGES FOR IMPROVED SHIP DETECTION
Author(s)
박주한; 양찬수; Ahmed Harun-Al-Rashid; Kazuo Ouchi
KIOST Author(s)
Park, Ju Han(박주한)Yang, Chan Su(양찬수)
Publication Year
2019-08-09
Abstract
Synthetic Aperture Radar (SAR) images contain different types of noises which restricts its wide application for the ocean surveillance. Therefore, this study focuses on removing several types of noises from SAR images. At first images were Fourier transformed to obtain frequency domain. Then, sidelobe noises from KOMPSAT-5, and scalloping and thermal noises from Sentinel-1 images were masked out by applying low-pass filter on the frequency domain. Then pixels affected by azimuth ambiguity in KOMPSAT-5 images were determined based on the distance and comparative brightness of the detected ships, and removed accordingly. This method is applied on 4 KOMPSAT-5 images and validated with the visual detection results of ships. The ship detection results without applying noise removal contains up to 59.26% false detections which were fully removed by the proposed method. Thus, the proposed noise reduction scheme has improved the accuracy of ship detection. Further improvement of the algorithm using more images is in progress.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/22539
Bibliographic Citation
IGARSS 2019, pp.1, 2019
Publisher
IEEE Geoscience and Remote Sensing Society
Type
Conference
Language
English
Publisher
IEEE Geoscience and Remote Sensing Society
Related Researcher
Research Interests

Satellite Oceanography,Marine Safety & Security,Remote Sensing,위성해양학,해양 안전 및 보안,원격탐사

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