Editing Sobel operator (section)

{{Short description|Image edge detection algorithm}}
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[[Image:Valve original (1).PNG|thumb|300px|right|A color picture of an engine]]
[[Image:Valve sobel (3).PNG|thumb|300px|right|The Sobel operator applied to that image]]

The '''Sobel operator''', sometimes called the '''Sobel–Feldman operator''' or '''Sobel filter''', is used in [[image processing]] and [[computer vision]], particularly within [[edge detection]] algorithms where it creates an image emphasising edges. It is named after [[Irwin Sobel]] and Gary M. Feldman, colleagues at the [[Stanford Artificial Intelligence Laboratory]] (SAIL). Sobel and Feldman presented the idea of an "[[Isotropy|Isotropic]] 3&nbsp;×&nbsp;3 Image Gradient Operator" at a talk at SAIL in 1968.<ref name="Sobel">Irwin Sobel, 2014, [https://www.researchgate.net/publication/239398674_An_Isotropic_3_3_Image_Gradient_Operator ''History and Definition of the Sobel Operator'']</ref> Technically, it is a [[Difference operator|discrete differentiation operator]], computing an approximation of the [[Image gradient|gradient]] of the image intensity function. At each point in the image, the result of the Sobel–Feldman operator is either the corresponding gradient vector or the [[norm (mathematics)|norm]] of this vector. The Sobel–Feldman operator is based on convolving the image with a small, separable, and integer-valued filter in the horizontal and vertical directions and is therefore relatively inexpensive in terms of computations. On the other hand, the gradient approximation that it produces is relatively crude, in particular for high-frequency variations in the image.