Real-time detection method of visible light remote-sensing image cloud field
A technology for remote sensing images and detection methods, which is applied in the fields of instruments, scene recognition, and computing, and can solve problems such as high computational complexity and unsatisfactory real-time cloud area detection.
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Embodiment 1
[0053] Embodiment 1: Example of detection of cloud areas containing large cloud areas
[0054] 1. Basic processing unit division
[0055] In order to control the processing granularity of the cloud area detection algorithm, the test image is first divided into non-overlapping G×G image sub-blocks. In this experiment, the test image is a panchromatic image, the pixel data bit depth is 8 bits, the spatial resolution is 2 meters, and the image block size G is set to 64.
[0056] 2. Whitening treatment
[0057] In order to maintain the invariance of feature extraction to illumination changes, the image sub-block is whitened, that is, all pixels in the image sub-block minus the mean value of the pixel value in the sub-block, divided by the standard deviation of the pixel value in the sub-block. The result of the whitening process is used as the input of the filter.
[0058] 3. Filtering based on unidirectional anisotropic Gaussian filter bank
[0059] Since the appearance of cl...
Embodiment 2
[0069] Embodiment 2: Example of detection of cloud areas containing small cloud areas
[0070] Its processing step is identical with embodiment 1. Figure 3(a) is the original remote sensing image containing a small cloud area, Figure 3(b) is the detection result of the cloud area based on the histogram feature of the visual word in six directions without dimensionality reduction, and Figure 3(c) is the detection result based on the single direction and The cloud area detection result of the visual word histogram feature without dimensionality reduction, Fig. 3 (d) is the cloud area detection result of the visual word histogram feature proposed by the present invention. By comparing Fig. 3(b), Fig. 3(c) and Fig. 3(d), the visual word histogram feature proposed by the present invention can achieve detection performance equivalent to that of the two variant feature extraction algorithms.
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