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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.
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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-07-13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."],[[["Calculates the spectral gradient of an image by finding the difference between spectral erosion and dilation."],["Utilizes a specified spectral distance metric (SAM, SID, SED, or EMD) and a structuring kernel for the calculations."],["Offers options to compute distances from the kernel's center pixel or the centroid of all pixels within the kernel."],["Based on the multidimensional morphological operations described by Plaza et al.(2002)."]]],[]]