A method for extracting a salient planar specific object from a remote sensing image

Abstract

The invention relates to a method for extracting a salient planar specific object in a remote sensing image, which is characterized in that the method comprises the following steps: 1) segmenting theimage; 2) selecting a small number of specific target samples, and realizing threshold extraction of potential specific target region P by estimating high-dimensional normal distribution parameters and enhance transformation operation; 3) utilizing that difference of the eigenvalues of the object and the adjacent object to extract a significant region S by a threshold value; 4) taking the region Kintersected by P and S as seed, and the region G coalesced by P and S as the region to be increased, and carrying out the region growth with the object as a unit to obtain the preliminary target extraction result T0; 5) By means of geometric and morphological features, the non-target region is further excluded from T0, and the final area-shaped specific target region is obtained. The method of the invention can quickly and effectively extract the seed object of the specific target area, and solves the problem of edge blur when extracting the prominent target. It is suitable for automatic extraction from remote sensing images of specific targets that emphasize area attributes, such as artificially cultivated areas.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, in particular to a method for extracting a salient surface specific target in a remote sensing image. Background technique [0002] Specific targets closely related to human activities, such as mining mines, ginseng cultivation areas, etc., present visually salient features in remote sensing images. In addition, this type of target is usually presented as a surface, and its area information has important reference value for ecological assessment, management, and related market assessment. Timely and accurate automatic acquisition of the area and spatial distribution of these prominent planar specific targets from remote sensing images is a very meaningful task compared to traditional field and market surveys with high cost and poor timeliness. [0003] Existing saliency-specific object extraction mainly includes supervised classification and pixel-based visual attention models. ...

AI Technical Summary

Problems solved by technology

Its disadvantage is that in sample selection, not only positive samples belonging to a specific target need to be included, but also negative samples that do not belong to a specific target need to be included. In practice, the types of negative samples are very complicated, which leads to the cost of this type of method in practical applications. high

This type of processing method has two main problems: (1) There is no distinction for salient objects, that is, any visually salient object will be extracted; (2) The limited pixel-based salient feature map calculation method leads to blurred edges , making the area less accurate

Retrieval of Chinese and foreign literature, this method has not been used in the prior art to extract the specific target of the salient surface

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