page_title: Sobel operator
section_title: Example comparisons
hierarchical_section_title: Sobel operator / Example comparisons
caption_attribution_description: English: Grayscale image of a brick wall &amp; bike rack convolved with a Roberts Cross operator.
context_page_description: 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 Feldman, colleagues at the Stanford Artificial Intelligence Laboratory. Sobel and Feldman presented the idea of an "Isotropic 3x3 Image Gradient Operator" at a talk at SAIL in 1968. Technically, it is a discrete differentiation operator, computing an approximation of the 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 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.
context_section_description: Here, four different gradient operators are used to estimate the magnitude of the gradient of the test image.
caption: Gradient magnitude from Roberts Cross operator
exif: {}