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                      "value": "Upper-diagonal elements of the structure tensor for each pixel in the input image."
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              "value": "Compute structure tensor using sum of squared differences."
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                      "value": "Standard deviation used for the Gaussian kernel, which is used as a weighting function for the local summation of squared differences. If sigma is an iterable, its length must be equal to "
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                      "value": "NOTE: 'xy' is only an option for 2D images, higher dimensions must always use 'rc' order. This parameter allows for the use of reverse or forward order of the image axes in gradient computation. 'rc' indicates the use of the first axis initially (Arr, Arc, Acc), whilst 'xy' indicates the usage of the last axis initially (Axx, Axy, Ayy)."
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              "value": "which is approximated by the weighted sum of squared differences in a local window around each pixel in the image. This formula can be extended to a larger number of dimensions (see "
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