High-resolution satellite image and rational polynomial parameter transformation method

Abstract

The invention relates to a high-resolution satellite image and rational polynomial parameter transformation method so as to adapt to requirements of a mapping workstation in the aspects of a data volume, an image angle and the like and ensure that accuracy after transformation still meets the mapping requirement. The high-resolution satellite image and rational polynomial parameter transformationmethod comprises the steps of: compiling a grid on an original image at a certain interval; in a set elevation range, replicating such grid at different elevations, and acquiring three-dimensional coordinates of each point on all the grids; when image space coordinates and the elevations are known, determining ground coordinates of each grid point by rational polynomial forward transformation; after a coordinate system of the image is transformed, determining new coordinates of all the grid points, wherein the new coordinates of the grid points correspond to object space coordinates; accordingto the transformed image, solving a normalized parameter of a rational polynomial after transformation; and when the normalized parameter is known, carrying out iteration on a corresponding relationship between the new coordinates of the grid points and the object space coordinates E, N and H to resolve a new rational polynomial parameter.

Description

technical field [0001] The invention relates to the field of surveying and mapping remote sensing, in particular to a high-resolution satellite image and a parameter transformation method thereof. Background technique [0002] With the advancement of sensor technology, electronic technology and earth observation technology, countries have successively launched many high-resolution remote sensing satellites to conduct all-round and all-weather observation of the earth. At present, the existing high-resolution satellites include 1.5-meter Spot7, 1-meter Ikonos, 0.5-meter Pleiades, 0.41-meter GeoEye, and 0.3-meter WorldView-3. The map has high precision; the single-scene image covers a large area and the mapping area is wide. However, due to the high resolution, the amount of image data has increased dramatically. A single image is generally about 2GB, and some even exceed 4GB, which reduces the processing speed of the computer and slows down the encryption and matching of aer...

AI Technical Summary

Problems solved by technology

However, due to the high resolution, the amount of image data has increased sharply. A single image is generally about 2GB, and some even exceed 4GB, which leads to a decrease in computer processing speed and slow encryption and matching

At present, the existing domestic mapping workstations do not support large image data enough. As the amount of data increases, mapping software cannot open high-resolution satellite images, or the display will appear stuck and instantaneous up and down parallax phenomena, affecting Mapping speed and accuracy

Images