Abstract
The adjacency effect can blur and reduce the contrast of satellite images. For low visibility, the adjacency effect has a crucial impact on submeter-scale spatial resolution optical (SM) satellite images. Therefore, SM satellite images are preprocessed with an atmospheric correction before performing visual interpretation and quantitative research. This atmospheric correction includes the adjacency effect (expressed by the average background reflectance, ABR) correction and atmospheric intrinsic reflectance correction. ABR is related to the spatial distance from the central pixel to its surrounding pixels (SDCS) and is affected by the reflectance difference between the central pixel and its surrounding pixels (RDCS). Existing methods to calculate ABR do not include the effect of RDCS. Therefore, in this study, we use equivalent average background reflectance (EABR) instead of ABR used in the 6S model. EABR considers the effects of the strengths of the aerosol optical depth (AOD), SDCS, and RDCS on the adjacency effect. Compared with ABR, EABR can better represent the adjacency effect in an SM satellite image. We develop an adaptive atmospheric correction algorithm (called adaptive-AC) based on EABR. The adaptive characteristic of adaptive-AC is that it can adjust the contribution factor (or weighted value) of the background pixel to the adjacency effect according to the SDCS and RDCS. The application of adaptive-AC to a panchromatic band image of WorldView-3 (WV-3) reveals that adaptive-AC can significantly improve image quality, with the reflectance of pixels in the corrected image processed by adaptive-AC being close to the actual reflectance. Comparison with the results of the atmospheric correction algorithm in the 6S model (6S-AC) indicates that adaptive-AC is more suitable for SM satellite image preprocessing than 6S-AC approaches. There is no clear theory or formula available to calculate the exact value of the adjacency effect range (Rad). Therefore, different Rad values are used in applying the adaptive-AC and 6S-AC. The results show that the larger is the Rad used to construct the adjacency effect model, the more satisfactory is the atmospheric correction.
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