Illumination-invariant completed LTP descriptor for cloud classification

Cloud classification plays an essential role in a large number of applications. However, this issue is particularly challenging due to the extreme appearance variations under different atmospheric conditions. In this paper, a novel descriptor named illumination-invariant completed local ternary pattern (ICLTP) is proposed for cloud classification. The proposed descriptor effectively handles the illumination variations by introducing illumination invariant factor. Furthermore, the Quadratic-Chi metric, which is more suitable for comparing the difference between two histograms, is applied instead of Chi-Square metric. The experimental results demonstrate the superior performance of our strategy on two challenging cloud databases. Besides cloud classification, we further validate the proposed ICLTP operator on traditional texture classification, which show the good generalization ability.