Remote sensing image preprocessing method

Abstract

The invention provides a remote sensing image preprocessing method. The method comprises a step of carrying out orthographic correction on input remote sensing images and a step of carrying out Gram-Schmidt fusion on orthographically corrected images. For each waveband of each image, a plurality of computing threads are executed in parallel on a GPU; and the images comprise single-scene low-resolution multispectral images MSS and high-resolution single-waveband images PAN. The method is based on a CUDA (Computed Unified Device Architecture) universal parallel computing architecture. Accordingto the method, the remote sensing images are preprocessed by utilizing the parallel processing capability of the GPU; and the orthographic correction and the Gram-Schmidt fusion algorithms in processing are improved; and therefore, the parallel processing of the remote sensing images on thousands of threads on the GPU is realized, and processing speed is greatly increased.

Description

technical field [0001] The invention relates to the technical field of remote sensing, in particular, to a method for preprocessing remote sensing images. Background technique [0002] Image preprocessing is the first and very important step in remote sensing applications, generally including geometric (ortho) correction, image fusion, image mosaic, atmospheric correction and other links. Among them, the low-resolution multispectral image MSS (usually four bands of red, green, blue and near-infrared) and the high-resolution single-band image PAN are respectively orthorectified based on geometric correction and digital elevation model. The processing flow of resampling and fusion to generate high-resolution multispectral images (referred to as "ortho + fusion") is one of the most basic and commonly used processing flows in image preprocessing. As the spatial resolution of remote sensing images increases to the meter level or even sub-meter level, the data volume of multispec...

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Problems solved by technology

And existing method is to process by CPU, owing to be subjected to the limitation of the core number of single machine processor (desktop or general graphics work station has several cores at most, high-end workstation has at most ten cores, and high-end multi-way server also only has several cores at most. Ten cores), when faced with such an order of magnitude, the preprocessing time is greatly increased, which cannot meet the requirements for fast processing of multi-view images

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