Color reconstruction method for optical remote sensing image based on convolutional neural network
An optical remote sensing image and convolutional neural network technology, applied in the field of image processing, can solve the problems of image color reconstruction, unsuitable images, and large amount of calculations, and achieve the effect of avoiding color inconsistency and good color reconstruction effect
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[0026] The embodiments and effects of the present invention will be further described below in conjunction with the accompanying drawings.
[0027] refer to figure 1 , the specific implementation steps of the present invention are as follows:
[0028] Step 1, obtain remote sensing image classification dataset Y and color remote sensing image X1.
[0029] Download the remote sensing image classification dataset Y and color remote sensing image X1 required for the experiment from the website;
[0030] The remote sensing image classification dataset contains 35 different categories, namely town, water flow, storage room, sparse forest, snow mountain, shrub, sea, sapling, beach, shelter forest, river, residential area, pipeline, parking lot, mountain, ocean, red Trees, lake shores, barren land, highways, green farms, forests, dry farms, deserts, dams, intersections, containers, coastlines, urban buildings, bridges, bare land, avenues, agricultural greens, airplanes and airport r...
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