TY - GEN
T1 - A new coastline extraction in remote sensing images
AU - Kun, Xing
AU - Yili, Fu
AU - Feng, Zhou
PY - 2012
Y1 - 2012
N2 - While executing tasks such as ocean pollution monitoring, maritime rescue, geographic mapping, and automatic navigation utilizing remote sensing images, the coastline feature should be determined. Traditional methods are not satisfactory to extract coastline in high-resolution panchromatic remote sensing image. Active contour model, also called snakes, have proven useful for interactive specification of image contours, so it is used as an effective coastlines extraction technique. Firstly, coastlines are detected by water segmentation and boundary tracking, which are considered initial contours to be optimized through active contour model. As better energy functions are developed, the power assist of snakes becomes effective. New internal energy has been done to reduce problems caused by convergence to local minima, and new external energy can greatly enlarge the capture region around features of interest. After normalization processing, energies are iterated using greedy algorithm to accelerate convergence rate. The experimental results encompassed examples in images and demonstrated the capabilities and efficiencies of the improvement.
AB - While executing tasks such as ocean pollution monitoring, maritime rescue, geographic mapping, and automatic navigation utilizing remote sensing images, the coastline feature should be determined. Traditional methods are not satisfactory to extract coastline in high-resolution panchromatic remote sensing image. Active contour model, also called snakes, have proven useful for interactive specification of image contours, so it is used as an effective coastlines extraction technique. Firstly, coastlines are detected by water segmentation and boundary tracking, which are considered initial contours to be optimized through active contour model. As better energy functions are developed, the power assist of snakes becomes effective. New internal energy has been done to reduce problems caused by convergence to local minima, and new external energy can greatly enlarge the capture region around features of interest. After normalization processing, energies are iterated using greedy algorithm to accelerate convergence rate. The experimental results encompassed examples in images and demonstrated the capabilities and efficiencies of the improvement.
KW - Active contour model
KW - Coastline extraction
KW - External energy
KW - Greedy algorithm
KW - Image contours
KW - Internal energy
KW - Remote sensing images
KW - Water segmentation
UR - https://www.scopus.com/pages/publications/84875657206
U2 - 10.1117/12.970478
DO - 10.1117/12.970478
M3 - 会议稿件
AN - SCOPUS:84875657206
SN - 9780819492777
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Image and Signal Processing for Remote Sensing XVIII
T2 - Image and Signal Processing for Remote Sensing XVIII
Y2 - 24 September 2012 through 26 September 2012
ER -