Due to the sub-meter higher spatial resolution of panchromatic satellite images, the imaging process is easily affected by atmospheric scattering and absorption and adjacency effect under low atmospheric visibility, resulting in blurred edges of image objects and reduced image quality, and seriously affects the accuracy of quantitative remote sensing application. Before the application of panchromatic satellite image, atmospheric correction should be carried out to improve image quality. At present, the conventional atmospheric correction software can not correct the panchromatic satellite image, so the digital image processing method is often used to improve the quality of panchromatic satellite image. However, the digital image processing method often brings the problems of noise and excessive enhancement while improving the image quality. Therefore, it is urgent to develop a set of atmospheric correction methods suitable for panchromatic satellite images, eliminate the influence of atmosphere and surrounding environment on the target pixel satellite entry pupil signal, recover the real surface information, and improve image quality in the panchromatic satellite image quantitative remote sensing application.
Taking the panchromatic satellite image of GF-2 as an example, this paper develops a set of atmospheric correction method for panchromatic satellite image by using the atmospheric radiative transfer model and the exponential decay point spread function. This method is simple to calculate, and fully considers the influence of atmospheric parameters (parameters of aerosol, water vapor, ozone, and other absorbing gases), spatial resolution, and adjacency effect between background pixels and target pixels on the entry pupil signal of target pixels, which further improves the image quality on the premise of ensuring the truth of panchromatic satellite image information. As an important evaluation index of an optical satellite imaging system, the modulation transfer function (MTF) can comprehensively and objectively characterize the sharpness of the image edge and the expression degree of spatial details, and its value can directly reflect the quality of imaging. Therefore, in order to comprehensively evaluate the quality of panchromatic satellite images after atmospheric correction, the traditional image quality evaluation indexes (clarity, contrast, edge energy, and detail energy) and MTF are simultaneously adopted in this paper to comprehensively and fully evaluate the atmospheric correction results.
The atmospheric correction method for panchromatic satellite images developed in this paper is used to correct the GF-2 panchromatic satellite images of Baotou calibration site under two atmosphere conditions: clean atmosphere and polluted atmosphere. The results show that whether the atmospheric conditions are polluted or clean, the visual effect of the corrected panchromatic satellite images has been improved, the contours of ground objects become clear, the texture information is more abundant, and the recognition of ground objects has also been significantly improved. For high resolution panchromatic satellite images, the atmospheric correction method ignoring the adjacency effect can only improve the image brightness, but does not improve image clarity much. Especially in the case of air pollution, the edge of ground objects in the corrected image is still relatively fuzzy, which is not conducive to the visual interpretation of the image and the extraction of ground objects contour. This further proves that adjacency effect correction is essential for high resolution panchromatic satellite images. By comparing the quality evaluation parameters of each image before and after correction, it can be seen intuitively that the clarity increases by at least 155%, the contrast increases by at least 115%, the edge energy increases by at least 247%, the detail energy increases by at least 204%, and MTF increases by at least 169%.
Based on the 6SV radiative transfer model, the atmospheric correction method developed in this paper combines the atmospheric point spread function based on the exponential decay model, and fully considers the influence of atmospheric parameters (parameters of aerosol, water vapor, ozone and other absorbing gases), spatial resolution, and the spatial distance between background pixels and target pixels on the adjacency effect. It can effectively remove the influence of atmosphere and surrounding environment on the satellite load entry pupil signal in the process of panchromatic satellite image imaging, recover the surface truth information in the imaging area which is covered by atmospheric influence, and fully improve the quality of panchromatic satellite image under low atmospheric visibility. After the evaluation of the corrected panchromatic satellite image quality, it is found that compared with the traditional image quality evaluation index, MTF can better reflect the improvement and promotion of the sub-meter panchromatic satellite image quality by the proximity effect correction, which highlights the indispensability of the adjacency effect correction in the atmospheric correction of the panchromatic satellite image. At the same time, the trend of MTF curve and the level of the value can reflect the spatial acuity of the image and the advantages and advantages of the image quality more comprehensively and objectively. Therefore, MTF index is recommended to be included in the image quality evaluation system when sub-meter satellite images (such as panchromatic satellite images) are evaluated.
