Development of a Fast Convergence Gray-Level Co-Occurrence Matrix for Sea Surface Wind Direction Extraction from Marine Radar Images

The new sea surface wind direction from the X-band marine radar image is proposed in this study using a fast convergent gray-level co-occurrence matrix (FC-GLCM) algorithm. First, sampled directly without need for interpolation due to algorithm’s application of GLCM polar co-ordinate system, which reduces inaccuracy caused by transformation. An additional process then merge convergence method with optimized so that circular transition between rough and fine estimates acquired, resulting accuracy improvement GLCM. Furthermore, algorithm will affect spatial distribution while calculating it, it can automatically resolve 180° ambiguity problem retrieved images. Finally, applied 1436 sequences collected coast East China Sea. Compared situ anemometer data, correlation coefficient as high 0.9268, RMSE 4.9867°. was also tested under diverse conditions. FC-GLCM results against adaptive reduced (ARM), energy spectrum (ESM), traditional (T-GLCM) produced best stability accuracy, decreased 91.6%, 67.7%, 18.1%, respectively.