Novel low-SNR sea-sky-line extraction algorithm

Liu Shijian; Wu Yingyue; Cai Nengbin

For SNR of sea-sky-line is low and there is a certain inclination so thay are difficult to extract, a new extraction algorithm was proposed. Firstly, the image preprocessing was taken by applying Laplacian template filtering to enhance waves on the surface, followed by order-statistics filters and morphologic closing. After the image preprocessing step, the SNR of sea-sky-line was enhanced. Finally, seeking for the inclined sea-sky-line by using a novel matrix, the matrix should be produced by scanning infrared image horizontally, the maximal element of the matrix identified the position and angle of the sea-sky-line. The experimental result shows that the method can locate sea-sky-line efficiently and correctly, requiring a few computation and be used for engineering applications. Innovations are the use of templates and morphological operators to improve SNR of sea-sky-line and find matrix can simply locate the position and angle of sea-sky-line, reducing the computational complexity.

1. Shanghai Key Laboratory of Scene Evidence,Shanghai 200083,China;

2. Shanghai Institute of Technical Physics of the Chinese Academy of Sciences,Shanghai 200083,China

Received Date: 2013-04-10

Rev Recd Date: 2013-05-03

Publish Date: 2013-12-25

Key words:

Abstract: For SNR of sea-sky-line is low and there is a certain inclination so thay are difficult to extract, a new extraction algorithm was proposed. Firstly, the image preprocessing was taken by applying Laplacian template filtering to enhance waves on the surface, followed by order-statistics filters and morphologic closing. After the image preprocessing step, the SNR of sea-sky-line was enhanced. Finally, seeking for the inclined sea-sky-line by using a novel matrix, the matrix should be produced by scanning infrared image horizontally, the maximal element of the matrix identified the position and angle of the sea-sky-line. The experimental result shows that the method can locate sea-sky-line efficiently and correctly, requiring a few computation and be used for engineering applications. Innovations are the use of templates and morphological operators to improve SNR of sea-sky-line and find matrix can simply locate the position and angle of sea-sky-line, reducing the computational complexity.

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[1]	Faraklioti M, Petrou M. Multiresolution versus single resolution horizon picking in 2D seismic images[C]//SPIE, 2004, 5238: 50-61.
[2]
[3]
[4]	Zhang Jinsuo, Song Liquan, Jin Minhui, et a1. Research on infrared small target detection technique based on bandpass filtering[J]. Infrared and Laser Engineering, 2002, 31(4): 294-597. (in Chinese)
[5]
[6]	Zhang Bing, Zhao Ningxia, Liu Weiting, et a1. Research on water-sky-line detection technique Bbased on wavelet transform[J]. Laser Infrared, 2005, 35(4): 297-299. (in Chinese)
[7]
[8]	Liu Songtao, Zhou Xiaodon, Wang Chenggang. Robust sea-sky-line detection algorithm under complicated sea-sky background[J]. Opto-Electronic Engineering, 2006, 33(8): 5-l0. (in Chinese)
[9]	Wen Peizhi, Shi Zelin, Yu Haibin. Automatic detection method of IR small target in complex sea background[J]. Infrared and Laser Engineering, 2003, 32(6): 590-593. (in Chinese)
[10]
[11]
[12]	Niu Zhaodong, Zeng Rongsheng, Chen Zengping. Low-SNR sea-sky-line extraction using fuzzy voting by local line segment[J]. Signal Processing, 2010, 26(3): 405-412. (in Chinese)
[13]	Gonzalez Rafael C, Woods Richard E. Digital Image Processing[M]. 2nd ed. Beijing: Publishing House of Electronics Industry, 2002.
[14]
[15]	Liu Shijian, Jiang Min, Zhuang Liang. A fast and effective algorithm for sea-sky-line extraction in infrared image[J]. Infrared Technology, 2011, 33(4): 230-233. (in Chinese)

Novel low-SNR sea-sky-line extraction algorithm

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