Ocean thermal feature recognition, discrimination, and tracking using infrared satellite imagery

A method for quantitatively measuring ocean surface movement, using sequential 10.8-μm-band AVHRR images, is presented. An ordered statistical edge detection algorithm is used to select ocean thermal pattern features by detecting and mapping gradients and at the same time discriminating between the water surface, land, and clouds. Use of edge detection to select features in this manner reduces the need to perform preprocess screening and masking to remove clouds and land. A constrained correlation based feature recognition scheme is then used to find the best match to the pattern feature in a subsequent image. Surface displacement direction and distance are calculated for each selected point with average period velocity being computed based on elapsed time