HISTOGRAM-BASED MORPHOLOGICAL EDGE DETECTOR

We present a new edge detector for automatic extraction of oceanograph ic (mesoscale) features present in infrared (IR) images obtained from the Advanced Very High Resolution Radiometer (AVHRR). Conventional edg e detectors are very sensitive to edge fine structure, which makes it difficult to distinguish the weak gradients that are useful in this ap plication from noise. Mathematical morphology has been used in the pas t to develop efficient and statistically robust edge detectors. Image analysis techniques use the histogram for operations such as threshold ing and edge extraction in a local neighborhood in the image. An effic ient computational framework is discussed for extraction of mesoscale features present in IR images. The technique presented here, the Histo gram-Based Morphological Edge detector (HMED), extracts all the weak g radients, yet retains the edge sharpness in the image. We also present new morphological operations defined in the domain of the histogram o f an image. We provide interesting experimental results from applying the HMED technique to oceanographic data in which certain features are known to have edge gradients of varying strength.