Abstract
The Advanced Very High Resolution Radiometer (AVHRR) images collected from NOAA polar orbiting operational satellites were used in this study. The Laplacian of the Gaussian (Mexican hat) wavelet transform can be used as an edge detector to separate the high/low sea surface temperature (SST) areas from ambient water. The histogram of each satellite image is first examined for ocean feature enhancement by gray scale. The enhanced image is then wavelet transformed with various scales to separate various texture or features. The Mexican hat wavelet is used as a band-pass-filter, and its first derivative as a threshold for feature detection. Heuristic edge linking methods are used to further enhance the images. Finally, a binary image can be produced in order to reduce the data volume. By overlaying sequential binary images from different imaging time, the evolution of mesoscale features such as fronts, oil spills, and eddies can be monitored by wavelet analysis using satellite data from subsequent passes.
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