Cloud-removing method for optical image

Abstract

The invention discloses an optical image cloud removal method. The reasonable demarcation layer number l is selected after the optical image covered by the cloud is processed with n-layer wavelet decomposition; the background information, the scenery information and the cloud noise are respectively distributed to the approximate coefficient, 1-l low-layer detail coefficient and the l+1 high-layerdetail coefficient as far as possible. Then the high-layer detail coefficient is reconstructed; the cloud noise is removed through the setting of the brightness threshold Delta. The low-layer detail coefficient is processed with wavelet packet decomposition to remove the residual cloud noise. Finally, the detail coefficient and the approximate coefficient are reconstructed to obtain the processedimage; wherein, n and l are both integers; n is more than l which is more than 1. the optical image cloud removal method can effectively retain the background information and the scenery information out of the cloud area, weaken or eliminate the influence caused by the cloud covering, highlight the scenery information and obtain the high quality processing effects. Because the optical image cloudremoval method provides quantitative indexes for determining the optimum demarcation layer number l, the brightness threshold Delta, and the detail coefficient weight w; the optical image cloud removal method has good operability.

Description

technical field [0001] The invention relates to a restoration method for optical remote sensing images affected by cloud occlusion. Background technique [0002] Remote sensing technology provides rich remote sensing image information for various fields such as military, forestry, geology, agriculture, resources, meteorology, environment and engineering site selection, and has become an indispensable driving force for the sustainable development of national economy and society. With the rapid development of computer technology and space technology, remote sensing technology has broad application prospects, and has spatial continuity and temporal sequence. So far, remote sensing technology is the only means that can provide dynamic observation data on a global scale. At present, most of the widely used remote sensing data are optical image data. Although optical images have the advantages of large amount of information, high resolution and stable images, at the same time, th...

AI Technical Summary

Problems solved by technology

That is to say, while the algorithm filters out the cloud noise, the low-frequency image background components are lost, and some useful high-frequency information is lost.

Moreover, there is no quantitative basis for the selection of each parameter, and the actual operation is difficult.

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