Color-guided enhancement of airborne laser scanning data

This paper suggests using color-guided depth enhancement algorithms of computer vision to improve the resolution of airborne laser scanning (ALS) point clouds for remote sensing applications. We use co-registered high resolution color images with nadir view to enhance the ALS data; and perform quantitative evaluation in form of RMSE considering the whole depth image as well as the depth discontinuities only. Investigated methods include joint bilateral filtering, Markov Random Field (MRF) optimization with first and second order smoothness terms, and anisotropic diffusion. RMSE results on discontinuities indicate that detail improvement performance of the selected methods on the depth discontinuities is not on a satisfactory level for airborne data. Anisotropic diffusion and MRF optimization are promising to provide better results with further adjustments on the smoothness terms.