Thick cloud remote sensing removal method and device
A remote sensing and solution technology, applied in image data processing, instrumentation, computing, etc., can solve problems such as limited repair ability of regular texture or structural information, and achieve the effect of excellent repair effect, good coherence, and fast reconstruction.
Inactive Publication Date: 2014-04-16
INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
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[0004] One of the purposes of the present invention is to solve the technical problem that the removal method of remote sensing thick clouds in the prior art requires multi-source images of the same area and has limited ability to repair regular texture or structural information in cloud images, and provide a method without resorting to Reference image, using only part of the known information in the original image, according to a certain algorithm or rule to repair the defect information remote sensing thick cloud removal method
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[0037] Preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.
[0038] refer to figure 2 , shows the method flow chart of the remote sensing thick cloud removal method in the preferred embodiment of the present invention. In this preferred embodiment, step s201 and step s202 obtain reliable elements in the image matrix M to be restored according to the data element "deterministic sampling" Set Ω and P Ω (M);
[0039] Step s203; start: Y 0 =0, "hot start" cycle i=0 step s204, set step size δ, algorithm cycle k=0, make soft threshold parameter τ=τ i ; Step s205, execute soft threshold operation X k+1 =D τ (Y k ); step s206, judge whether the relative reconstruction error is less than ε, if so, execute step s212, if not, execute step s207; step s207, update Y k+1 =Y k +δP Ω (M-X k+1 ); Step s208, k++; Step s209, judge whether k is greater than maxiter, if not execute step s205 again; If so, then e...
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The invention discloses a thick cloud remote sensing removal method and device and belongs to the technical field of image processing. The thick cloud remote sensing removal method comprises the following steps of s101, acquiring a reliable element set from a matrix of images to be recovered through deterministic sampling; s102, setting step length and soft threshold parameters according to a singular value and threshold value shrinkage iterative algorithm; s103, performing shrinkage iteration through the singular value and threshold value shrinkage iterative algorithm to reconstruct an original image matrix; s104, judging whether a relative reconstruction error is smaller than the preset error; s105, adding one time on iterations; s106, judging whether the number of iterations is the largest; s107, outputting the reconstructed image matrix. By means of the thick cloud remote sensing removal method, defect information caused by pollution, damage, blocking or the like can be repaired well, information can be recovered, detail texture information is remained, and consistency of image structures is kept.
Description
technical field [0001] The invention relates to the technical field of image processing, in particular to a remote sensing thick cloud removal method and device thereof. Background technique [0002] When remote sensing images are acquired, they are often blocked by clouds, which makes some ground object information in the images missing, which in turn causes great difficulties for the subsequent analysis and interpretation of remote sensing images. Therefore, it is of great significance to remove the clouds in remote sensing images and restore the details of the original ground features. The declouding method based on sequential images represented by image fusion method requires multi-source images of the same area, and requires that the cloud areas between images do not overlap and solve the problem of possible radiation differences, which limits its practicability. In the prior art, a support vector machine-based remote sensing image thick cloud removal method is also pr...
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Inventor 孟樊杨晓梅周成虎
Owner INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS