Sea-surface temperature chart enhancement in frontal zones

Abstract

Infrared and microwave satellite images used for sea-surface temperature (SST) retrieval often have distortions such as noise and blurring of thermal front lines that decrease the quality of SST charts. In order to solve this problem, it is proposed to use an approach based on the Mumford–Shah model that approximates an image with a piecewise smooth function. In order to combine the advantages of the proposed approach and conventional methods for noise filtering and image restoration it is proposed to divide images into flat and frontal zones and process them separately. The SST quality is enhanced by the use of edge-preserving noise filtering and restoration algorithms. The latter use the features of radiometers and different stages of the SST construction procedure to improve their accuracy. The images obtained using the MTSAT/VISSR, METEOR-M/MSU-MR, and AQUA/AMSR-E radiometers are used for testing the developed approach.