Self-adaptive valley and ridge line extraction method and system based on scale space

Abstract

The invention provides a self-adaptive valley and ridge line extraction method and system based on a scale space. The self-adaptive valley ridge line extraction method comprises the following steps: firstly, carrying out oversampling on an original DEM (Digital Elevation Model) to serve as processed initial DEM, and establishing a zeroth group of scale space according to the initial DEM; according to a total layer number of a pyramid, firstly selecting the DEM with a highest spatial scale in the zeroth group of scale space as the bottom layer of the pyramid, then, carrying out downsampling on the zeroth layer of DEM, correspondingly establishing a first group of scale space, and selecting the DEM with the highest scale as the first layer of the DEM pyramid and so on; and starting with the top layer of the DEM pyramid to carry out self-adaptive multi-angle topographic section elevation extremum method extraction, carrying out postprocessing to obtain a ridge line and a valley line, and finally, carrying out the layer-by-layer refining extraction of a result. Compared with the prior art, the self-adaptive valley and ridge line extraction method not only can give both consideration to the integral tendency and the detail change of ridge (valley) extraction, guarantees extraction precision, but also can quickly obtain an extraction result and guarantee extraction efficiency.

Description

technical field [0001] The invention belongs to the technical field of digital terrain analysis, and relates to a method for extracting adaptive valley and ridge lines based on scale space. Background technique [0002] Digital elevation model (Digital Elevation Model, referred to as DEM) is a discrete mathematical representation of the earth's surface, and it is also one of the core data for three-dimensional spatial data processing and digital terrain analysis in remote sensing and geographic information systems. Ridge lines and valley lines are important dividing lines that can be extracted from digital elevation models to represent changes in mountain terrain, and have important applications in terrain representation, digital terrain analysis, surveying and engineering design. Therefore, extracting ridgelines and valleylines automatically and efficiently from DEM has always been an important topic in the field of digital terrain analysis. [0003] Existing extraction me...

AI Technical Summary

Problems solved by technology

The overall algorithm has a strong ability to resist noise, but for mountains with small undulations, the extraction effect is poor, and the amount of calculation is large, and the amount of calculation of the algorithm increases in a quadratic relationship with the increase in the number of regular grids

These defects make this method inconvenient for the extraction of ridgelines and valley lines

Local algorithms include terrain section elevation extremum method, surface fitting method, etc. The main characteristics of local algorithms are small amount of calculation and fast speed, but they cannot take into account the overall change law of terrain, so that the extraction results will be missed. And it is easily affected by noise, which will bring inconvenience to the correct determination of subsequent ridge lines and valley lines

These two types of methods cannot take into account the whole and details, accuracy and efficiency, so they cannot meet the efficiency and accuracy requirements for automatic extraction of ridge lines and valley lines

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