A measure is proposed based on the information theory and geostatistics to evaluate information content in remotely sensed images. The method is based on the additive noise model and maximum mutual information.These factors affecting the information content have been taken into account, such as noise, spatial correlation and so on. It is suitable for measuring the information content in optical images that have robust spatial correlation with different land cover types. An experiment was performed on a Landsat TM image with three different kinds of land cover types (city, farmland and mountain). The result shows that city has the most information content. It also proves that there is a log positive correlation between information content and the variance of the images.
ZHANG Ying
,
ZHANG Jingxiong
. Measure of Information Content of Remotely Sensed Images Accounting for Spatial Correlation[J]. Acta Geodaetica et Cartographica Sinica, 2015
, 44(10)
: 1117
-1124
.
DOI: 10.11947/j.AGCS.2015.20140417
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