Possion method for removing cloud from optical remote sensing image

Abstract

The invention discloses an Poisson method for cloud removing of optical remote sensing image, which comprises the steps of: selecting basic base map image and alternative image which meet treatment of image removing cloud layer by using image selector; identifying and detecting the range of cloud layer coverage area through cloud area identification unit, making formation cloud area identification template respectively; using the base map image, the alternative image and cloud area identification plate by pyramid processing to construct multi-level similar unit; proceeding Cloud area pixel detection progressively and connected cloud area detection to each grade pyramid, and alternative image detection to connected cloud area of cloud identification template which is processing; seeking linear transformation parameter by using image gradient field regulation pixel to corresponding cloudless point department of the alternative image and basic base map image around connected cloud area; taking non-cloud megapixel point around connected cloud area of basic base map image as Dirichlet boundary condition, and linear transformation alternative area image gradient field as guide field, proceeding fusion processing to the image by using Poisson removing cloud processing algorithm.

Description

technical field [0001] The invention relates to an image preprocessing method in the field of remote sensing image processing, in particular to a Poisson method for cloud removal of optical remote sensing images. Background technique [0002] When acquiring optical remote sensing images, it is difficult to avoid the occlusion of the acquired images by clouds caused by cloudy and rainy weather. Therefore, it is necessary to remove the clouds in the multi-temporal series of images according to the characteristics that the clouds are always in motion. Therefore, a variety of remote sensing image cloud removal processing methods have emerged as the times require. Generally, various image restoration processes can be performed on a single image when thin clouds or mist appear in the image. However, when there are thick clouds in the image and the coverage area is large, any method for restoring the original image will be weak. Therefore, people consider to use the complementary...

AI Technical Summary

Problems solved by technology

Although simple inversion and substitution can restore the original image, due to the difference in tone between images of similar phases, there will be obvious traces of the edge of the substitute area after simple inversion and substitution. To eliminate these traces, human-machine Interactive operation, using image stretching technology to adjust pairwise images to improve visualization, but it will still affect further quantitative application analysis

Therefore, it is necessary to develop an algorithm, a complete set of methods and a processing flow for removing clouds from remote sensing images in order to address the obvious traces of image mosaicing and the inability to achieve seamless splicing effects when cloud removal and restoration of the original image are performed on large thick clouds in the covered area.

At present, this image cloud removal preprocessing method has not seen a suitable method that can be used in practical applications

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