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Computes the spectral gradient over all bands of an image (or the first band if the image is Array typed) by computing the per-pixel difference between the spectral erosion and dilation with a given structuring kernel and distance metric. See: Plaza, Antonio, et al. 'Spatial/spectral endmember extraction by multidimensional morphological operations.' IEEE transactions on geoscience and remote sensing 40.9 (2002): 2025-2041.
Usage
Returns
Image.spectralGradient(metric,kernel,useCentroid)
Image
Argument
Type
Details
this:image
Image
The input image.
metric
String, default: "sam"
The spectral distance metric to use. One of 'sam' (spectral angle mapper), 'sid' (spectral information divergence), 'sed' (squared Euclidean distance), or 'emd' (earth movers distance).
kernel
Kernel, default: null
Connectedness kernel. Defaults to a square of radius 1 (8-way connected).
useCentroid
Boolean, default: false
If true, distances are computed from the mean of all pixels under the kernel instead of the kernel's center pixel.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-07-13 UTC."],[[["\u003cp\u003eComputes the spectral gradient of an image by calculating the difference between spectral erosion and dilation using a specified kernel and distance metric.\u003c/p\u003e\n"],["\u003cp\u003eOffers a choice of four spectral distance metrics: SAM, SID, SED, and EMD.\u003c/p\u003e\n"],["\u003cp\u003eAllows customization of the connectedness kernel and the method of distance calculation (from the kernel's center or centroid).\u003c/p\u003e\n"],["\u003cp\u003ePrimarily used for spatial/spectral endmember extraction in hyperspectral images, as described in the cited research by Plaza et al.\u003c/p\u003e\n"],["\u003cp\u003eOperates on all bands of multi-band images or the first band of Array-typed images.\u003c/p\u003e\n"]]],[],null,["# ee.Image.spectralGradient\n\nComputes the spectral gradient over all bands of an image (or the first band if the image is Array typed) by computing the per-pixel difference between the spectral erosion and dilation with a given structuring kernel and distance metric. See: Plaza, Antonio, et al. 'Spatial/spectral endmember extraction by multidimensional morphological operations.' IEEE transactions on geoscience and remote sensing 40.9 (2002): 2025-2041.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|---------------------------------------------------------------------|---------|\n| Image.spectralGradient`(`*metric* `, `*kernel* `, `*useCentroid*`)` | Image |\n\n| Argument | Type | Details |\n|---------------|-------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| this: `image` | Image | The input image. |\n| `metric` | String, default: \"sam\" | The spectral distance metric to use. One of 'sam' (spectral angle mapper), 'sid' (spectral information divergence), 'sed' (squared Euclidean distance), or 'emd' (earth movers distance). |\n| `kernel` | Kernel, default: null | Connectedness kernel. Defaults to a square of radius 1 (8-way connected). |\n| `useCentroid` | Boolean, default: false | If true, distances are computed from the mean of all pixels under the kernel instead of the kernel's center pixel. |"]]
