Laser & Optoelectronics Progress, Volume. 57, Issue 16, 160002(2020)
Sea-Sky Line Detection Methods: An Overview
Figures & Tables(16)
![Sea-sky line of visible images of sea and air background. (a) Horizontal sea-sky line[7]; (b)inclined sea-sky line[16]](/Images/icon/loading.gif){kind=icon}
Fig. 3. Four typical panoramic sea-sky lines in visual images of sea and air background. (a) Intact; (b) partially lost; (c) blurred; (d) extensively lost
Fig. 4. Infrared images of sea and sky background. (a) Gradient belt; (b) high contrast; (c) low contrast
Fig. 5. Interference images of sea and sky background. (a)(d) Sea clutter image and its infrared image; (b)(e) strong reflected light image and its infrared image; (c)(f) cloud interference image and its infrared image
Fig. 6. Low-quality images of sea and sky background. (a) Visible light image; (b) infrared image
Table 1. Characteristics of ordinary visible images of sea and air background
View tableTable 1. Characteristics of ordinary visible images of sea and air background
Region Location Characteristic Sky background region Above The reflection is strong and the brightness is large Sea-sky line region Middle A horizontal or inclined line of pixel gradient maximum runs through the entire image Sea surface background region Below The reflection is weak and the brightness is low
Table 2. Characteristics of visible panoramic images of sea and sky background
View tableTable 2. Characteristics of visible panoramic images of sea and sky background
Region Characteristic Panoramic equipment imaging region [ 34 ]The complexity of the panoramic image background increases and the sea antenna is fractured Sky background region The reflection is strong and the brightness is large Sea-sky line region An ellipse or circle of pixel gradient maximum runs through the entire image (with a break) Sea surface background region The reflection is weak and the brightness is low
Table 3. Characteristics of infrared images of sea and sky background
View tableTable 3. Characteristics of infrared images of sea and sky background
Region Location Characteristic Sky background region Above The reflection is strong and the brightness is large Sea-sky line region Middle In the figure, the regions with large changes in gray level and the sea-sky boundary zone with low brightness gradually run through the whole background infrared image (with blurred) Sea surface background region Below The reflection is weak and the brightness is low
Table 4. Characteristics of sea-sky line in different images
View tableTable 4. Characteristics of sea-sky line in different images
Image type Characteristic Image of ordinary visible sea-sky background A horizontal or inclined line of pixel gradient maximum runs through the entire image Panorama image of ordinary visible sea-sky background An ellipse or circle of pixel gradient maximum runs through the entire image (with a break) Infrared image of sea-sky background In the figure, the regions with large changes in gray level and the sea-sky boundary zone with low brightness gradually run through the whole background infrared image (with blurred)
Table 5. Summary of disturbance characteristics, disturbance factors and suppression methods
View tableTable 5. Summary of disturbance characteristics, disturbance factors and suppression methods
Interference characteristic Interference factor Suppression method Linear edge characteristic Sea clutter, strong light reflection, clouds Nonlinear segmentation, region segmentation, double threshold segmentation, multi-scale wavelet transform, Gaussian smoothing filtering Low imaging quality Weather conditions (rain, snow, fog), optical distortion, USV system shaking Laplace sharpening operator, multi-foot wavelet analysis Others Image occlusion of panoramic equipment region Fractal dimension calculation, full resolution algorithm
Table 6. Summary of generation method of sea-sky line for linear model
View tableTable 6. Summary of generation method of sea-sky line for linear model
Method Advantage Disadvantage Environmental adaptability Linear fitting based on RANSAN Small amount of calculation and good real-time performance The selection of candidate points is susceptible to environmental interference Based on gradient significance High detection efficiency Poor noise resistance, not considering the sea antenna tilt Poor environmental adaptability Based on OTSU segmentation Small computation and good real-time performance The threshold value is more sensitive and the ability to resist noise is poor Based on the Hough transform High accuracy The calculation amount is large, the real time is poor, the engineering practicality is low Strong environmental adaptability Based on Seam Carving High detection accuracy Large amount of calculation Our method Small amount of calculation and high accuracy Due to environmental interference, the detected sea-sky line is not strictly linear Good environmental adaptability
Table 7. Summary of generation method of panoramic sea-sky line
View tableTable 7. Summary of generation method of panoramic sea-sky line
Method Advantage Disadvantage Environmental adaptability Circle fitting High detection accuracy The prior radius is not easy to obtain, the calculation is large, and the real-time is poor Strong environmental adaptability Ellipse fitting When the ellipticity is large, the algorithm fails, the computation is large, and the real-time performance is poor
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Tianwei Feng, Jinqing Liu, Jinchao Xiao, Junfeng Xiong. Sea-Sky Line Detection Methods: An Overview[J]. Laser & Optoelectronics Progress, 2020, 57(16): 160002
Paper Information
Category: Reviews
Received: Nov. 6, 2019
Accepted: Jan. 9, 2020
Published Online: Aug. 5, 2020
The Author Email: Jinqing Liu (jqliu8208@fjnu.edu.cn)
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