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Irwin Sobel | |
|---|---|
| Born | Irwin Sobel September 12, 1940 New York City |
| Occupation | Scientist |
| Nationality | American |
| Alma mater | MIT |
| Notable works | Sobel operator (1968) |
| Spouse | Ceevah Sobel |
Irwin Sobel (born September 12, 1940) is a scientist and researcher in digital image processing.
Irwin Sobel was born in New York City. He graduated from MIT in 1961 and did his Ph.D. research at the Stanford Artificial Intelligence Project (SAIL) with thesis Camera Models and Machine Perception. [1] His Ph.D. advisor was Jerome A. Feldman. [2]
Starting in 1973, he spent nine years doing postdoctoral research at Columbia University. After 1982, he worked as a Senior Researcher at HP Labs. [3] [4]
In 1968, Sobel gave a talk entitled "An Isotropic 3x3 Image Gradient Operator" [5] at SAIL; this method became known as the Sobel operator. It was developed jointly with a colleague, Gary Feldman, also at SAIL.
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 "Isotropic 3 × 3 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.
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