A method for removing clouds and fog from a single remote sensing image

Abstract

The invention discloses a method for removing clouds and fog from a single remote sensing image, which includes the following steps: first perform gamma correction on the original image to improve the clarity and image contrast of the scene part; allocate the cloud and scene data to wavelet decomposed data respectively. High-level and low-level detail coefficients; calculate the dark channel map of the high-level detail coefficient, perform a weighting process with a weight greater than 1, and obtain the cloud coefficient after normalization; for the high-level detail coefficient, invert its reconstructed map and the cloud coefficient. Multiply them together to remove the clouds and fog while retaining the scenery. For the low-level detail coefficient, multiply its reconstruction image with the amplified result of the cloud layer coefficient, and superimpose the original low-level detail coefficient reconstruction image to highlight the scene information under the cloud layer; the processing results of the two parts of the detail coefficient and the approximate coefficient are repeated The compositions are superimposed to obtain the final processing result. While weakening the cloud coverage, the invention improves the clarity of the scenery under the clouds and better retains the information of the scenery outside the cloud area.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and relates to an image enhancement method for removing clouds and fog from a single remote sensing image. Background technique [0002] With the development of the aerospace industry, the ground remote sensing imaging technology is increasingly serving all walks of life in socialist construction, and plays an important role in promoting the stable development of the national economy and ensuring national social security. In the process of ground imaging, clouds and fog are common sources of interference. Remote sensing images containing clouds and fog have low contrast, unclear scenery and poor readability. Using digital image processing technology to reduce the influence of clouds and fog in remote sensing images, improve image clarity and highlight important information is of great significance for improving the efficiency of remote sensing satellite surveying earth res...

AI Technical Summary

Problems solved by technology

However, for remote sensing images with local thick clouds, the color of the scene will be distorted after using this algorithm

On this basis, the wavelet threshold algorithm performs threshold processing on the high-level detail coefficients according to the characteristics of the brighter cloud layer. While deleting the cloud, it can better retain the information outside the cloud area, but the processing result has obvious boundaries, and the visual effect needs to be improved.

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