Seawater pollution area identification method and device based on high-resolution remote sensing image

Abstract

The invention discloses a seawater pollution area identification method and device based on a high-resolution remote sensing image, and belongs to the field of digital image processing. The method comprises: firstly, performing sea-land automatic classification on remote sensing images through a supervised learning algorithm, a classification result can reach a high precision level through processiterative clustering, and meanwhile, compared with an existing sea-land boundary analysis and classification method, the operand being small; then, using the chlorophyll concentration difference andthe brightness difference of pollutant shadows existing between the marine pollution area and surrounding seawater; combining a normalized vegetation index related to chlorophyll, a normalized water body shadow index related to brightness, a segmentation-based image interpretation thought and a human eye vision-based saliency mechanism in remote sensing interpretation; through threshold segmentation, realizing extraction of a marine pollution area, respectively extracting an area with excellent water quality and a severely polluted area, and further obtaining a pollution transition area. The method provided by the invention provides convenient and accurate reference for marine pollution prevention and treatment.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and in particular relates to a method and equipment for identifying seawater polluted areas based on high-resolution remote sensing images. Background technique [0002] Today, as the global land resources are increasingly tense and the environment is deteriorating, countries all over the world are turning their attention to the ocean. The development of marine resources and the development of marine economy have become an important pillar of the national economy of coastal countries and the forefront of sustainable development strategies. While modern ocean development brings huge economic benefits, it also brings a series of resources and ecological environment problems. At present, the pollution of the marine environment is becoming more and more serious, and the ecological environment is also becoming worse and worse. Marine economic industries such as marine fishery and mar...

AI Technical Summary

Problems solved by technology

However, in these methods, there are constraints such as the large amount of calculation of the convolutional layer of the deep learning convolutional neural network model, high requirements for computing equipment, huge capital investment, and the need for guidance from professional and technical personnel; and the Grab-Cut image segmentation algorithm focuses on solving the original There are problems such as the accuracy of the remote sensing image algorithm segmentation scale and level, the lack of the "segmentation-classification" link, and the lack of discussion on the classification and identification of specific pollutants

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