Abstract:

The study on information extraction of settlements has important realistic significance for territorial planning and human security. Currently proposed settlements detection algorithms possibly detect sparse vegetation as settlements, thus degrading the detection accuracy. In order to obtain an efficient and high-accuracy detection method, the paper gives an improved model based on the analysis of the rotation-invariant texture of remote sensing images. Firstly, the morphological top-hat is applied to strengthen the spectrum and the interference of scattered vegetation is effectively suppressed. Secondly, by introducing an asynchronous communication model based on MPI (Message Passing Interface) and OpenMP, a parallel processing of the improved algorithm is realized successfully, which improves the efficiency of the algorithm. The experiment shows that this parallel algorithm improves detection accuracy and robustness, as well as solves the computational problem of large remote sensing images effectively.

Key words: settlement detection;gray-level co-occurrence matrix;texture;rotation-invariant;Top-Hat transformation;parallel computing