High-resolution remote sensing image change detection method based on multi-scale segmentation and fusion
A multi-scale segmentation and remote sensing image technology, applied in the field of hyperspectral remote sensing images, can solve the problems of inability to guarantee the integrity of detection results, low detection accuracy of high-resolution remote sensing images, etc., to improve accuracy, ensure integrity, and improve detection accuracy Effect
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specific Embodiment approach 1
[0012] Specific implementation manner 1: The method for detecting changes in high-resolution remote sensing images based on multi-scale segmentation and fusion described in this embodiment, the specific process of the detection method is:
[0013] Step 1. Use a multi-scale segmentation algorithm to segment the multi-temporal high-resolution remote sensing image at a spatial scale. The spatial scale is divided into two parts: coarse scale and fine scale, and appropriate shape factors are selected to use top-down regional heterogeneity Gender guidelines to merge;
[0014] Step 2. Perform feature extraction on the object angle of the target in each scale image segmented in Step 1, use the object feature to describe the object itself, and then perform vector analysis relative to remote sensing images in other phases to obtain object difference maps of multiple scales ;
[0015] Step 3. Perform change information extraction and fusion on the object difference map of multiple scales obtai...
specific Embodiment approach 2
[0021] Specific implementation manner 2: This implementation manner further illustrates the implementation manner 1. The specific method of using a multi-scale segmentation algorithm to perform spatial scale segmentation on multi-temporal high-resolution remote sensing images is:
[0022] Multi-scale segmentation uses a top-down region merging algorithm based on minimum heterogeneity to obtain image segmentation sequences of different scales of the input image, and combines shape heterogeneity to obtain merged regions. The representation of heterogeneity is:
[0023]
[0024] Where h total Represents overall heterogeneity, Indicates the weight of spectral heterogeneity, satisfying h c And h s Represents spectral heterogeneity and shape heterogeneity respectively, and satisfies:
[0025]
[0026]
[0027] among them, Indicates the weight of each band, the number of bands is c, σ c Indicates the standard deviation of each spectral band; Represents the smoothness weight, h sm And h...
specific Embodiment approach 3
[0038] Specific embodiment 3: This embodiment further explains the first or second embodiment. The multi-scale is divided into coarse scale and fine scale, the scale parameter of the fine scale is 10-50, and the scale parameter of the coarse scale is 50-100.
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