To improve the quality of the sea surface image under foggy weather, we propose an innovative single-image defogging algorithm based on the dark channel prior principle. The median filter is combined with the minimum filter for the purpose of obtaining accurate dark channel values in areas where the depth of field changes sharply. Then, the algorithm constructs a fog density detection model to obtain the atmospheric light value from the dense fog area and effectively eliminate the interference of bright spots. Subsequently, the atmospheric scattering model is applied to obtain a preliminary fog-free image. Finally, an adaptive logarithmic mapping algorithm is introduced to enhance the visual effect of the defogged image. Experimental results show that the proposed algorithm can effectively improve image quality degradation and avoid halos in the intersection region of sky and sea, Moreover, the method does not require guided filtering for transmittance refinement, which greatly improves the execution speed of the algorithm.
The use of wind imaging interferometer to retrieve wind field information requires high accuracy of the instrument in phase shift. Traditional wind field inversion algorithms invert wind field information such as wind speed and temperature based on equal phase-shift interferometers. In actual situations, the phase shift of the wind imaging interferometer does not perfectly meet the design requirements, producing inversion result errors. In this paper, the inversion algorithm of an arbitrary phase shift wind imaging interferometer is studied, and the feasibility of the AIA (advanced iterative algorithm) inversion algorithm is verified under the condition of low accuracy of the instrument phase shift. The comparison of the inversion results of the AIA algorithm in wide-field interference and non-widefield interference are respectively discussed. The influence of the unevenness of the strip system caused by the temperature distribution on the inversion accuracy of the AIA algorithm is analyzed. The conclusions of this paper can provide theoretical support for phase-shifting calibration of wind imaging interferometers and wind field information inversion in low-precision instrument.
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