Method for identifying characteristic land categories of ocean remote sensing images of coast on basis of semi-supervised learning

Abstract

The invention discloses a method for identifying characteristic land categories of ocean remote sensing images of a coast on the basis of semi-supervised learning and belongs to the field of identification of semi-automatic remote sensing images. The method comprises the following steps of: selecting a marking sample for each type of characteristic ground objects; constructing a dividing result facing to the remote sensing images of an object; computing an initial estimation value of probability that pixels of all samples are subordinate to the characteristic land categories and computing theprobability that sample data falls under components of the characteristic land categories; amending a probability image by using a characteristic space rule; judging the characteristic land categories which the remote sensing images belong to, realizing the identification of the characteristic land categories and outputting an identification result drawing. The method is combined with the priori knowledge and the statistical property of the data and can guide the data mining process by the topographical priori knowledge. Practice proves that the algorithm can effectively carry out classification of the remote sensing images to obtain a satisfying result, has the characteristics of high efficiency and high accuracy and can be directly used for maintaining and updating remote sensing thematic information of all levels of fundamental geographic information databases in China.

Description

technical field [0001] The invention relates to a method for identifying feature landforms of remote sensing image data, in particular to a method for identifying feature landforms of coastal ocean remote sensing images based on semi-supervised learning. Background technique [0002] As a non-contact observation technology, remote sensing has a long history. The remote sensing image data provided by it has the advantages of high timeliness, wide coverage, and rich information. It has been widely used in land use, resource exploration, and ecological environment. Monitoring, and the identification of coastal and marine features and land types are playing an increasingly important role in the development of society and economy. The coastal area is the core area of ​​social and economic development. With the strengthening of marine economic development, the land use, sea area use and environmental changes in the coastal area are also changing with each passing day. In order to...

AI Technical Summary

Problems solved by technology

However, since there is no input of prior knowledge at all, the results of unsupervised methods are difficult to directly serve as outcome data products

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