Using Spectral and Spatial Information Coupled with Mathematical Morphology for Oil Spill Detection in Multispectral Imagery

• Main Authors: Ling-Ling Tsao, 曹伶伶
• Other Authors: Hsuan Ren
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/68870031589119245349

碩士 === 國立中央大學 === 太空科學研究所 === 97 === Oil spill on the sea surface which is usually produced by human activities is disastrous to the ecological environment. In recent years, the technology for sea transportation is improvement. The export and import via marine transit are more and more frequently, the oil spill events are sometimes along with the process. How to detect, monitor and track the oil spill are always very important tasks. Due to oil spill often occur in open sea, remotely sensed image provides an effective technology to monitor the sea area. But the oil spill usually only occur in a very small area in the image. How to detect the oil spill on the sea surface is a challenge problem. Using the remotely sensed images to detect this unwelcomed hazard material on sea surface is a convenient and effective approach. This study focuses on the detection of oil slick on sea surface using multi-spectral imagery technology. Since the oil spill area is usually very small compare to the sea area in the image scene, it can be considered as anomaly. By using anomaly detection algorithm, the oil spill can approximately figure out, but there are still some marine phenomena to interference the result. In order to discriminate oil slick from the other interferences, spatial features are introduced into anomaly detection. Furthermore, we also adopt mathematical morphology to filter through the maintain noise further. Therefore, our proposed method is to employ the spatial features of oil spill and combine with spectral information and mathematically morphologic operation to improve the oil spill detection.　 In the experiment, we adopt SPOT multispectral images for performance analysis.