Atmospheric Scattered Light Field Sampling for Improving Reconstruction Efficiency

Light field (LF) atmospheric descattering methods using multi-view images from camera arrays offer significant advantages for solving strong scattering due to their ability in exploiting high-dimensional light information. However, the relationship between performance and scattered LF sampling rate (i.e., the density of samples per unit area) is an unknown coupling, affecting acquisition and processing complexity. In this paper, we define the minimum atmospheric scattered LF sampling rate under optimal descattering quality, based on attenuated spectral support in scattering scenarios derived from the proposed atmospheric point spread function (APSF). The proposed APSF integrates the camera model, radiative transfer equation, and modified generalized Gaussian distribution (GGD) to describe multiple scattering. For any scattering parameters, the proposed APSF can be directly derived without infinite series, ensuring full adaptability to all acquisition systems through the integration of system model. Combining APSF with scene and acquisition system information, the scattered LF spectrum is determined, and consequently the minimum atmospheric scattered LF sampling rate is derived for the first time. Experimental results demonstrate the accuracy, effectiveness, and robustness of the proposed atmospheric scattered LF sampling theory through comparisons of atmospheric descattering performance across different LF sampling rates, object types, scene depths, and scattering intensities. The proposed method achieves a reduction in the number of acquisition cameras by an average of 78.4% while maintaining processing quality, which significantly enhances the applicability of LF atmospheric descattering methods.