Performs a Sobeledge enhancement of an image.
NOTE: For horizontal line enhancement only, set the keyword Row = 0 to disable the vertical line enhancement.
'zero'
) Valid strings are:
'zero'
Sets the border of the output image to zero. (Default)
'copy'
Copies the border of the input image to the output image.
TIP: Use the No_Clip keyword to avoid overflow conditions.
'abs'
, 'phase'
, and 'value'
. The Return keyword is used with the Row and Col keywords per the following table. (Default: 'abs'
)
NOTE: For vertical line enhancement only, you must disable the horizontal line enhancement by setting the Col keyword to 0.
Scale If set, each gradient is scaled by the factor 0.25; otherwise, no scaling is performed.
Zero_Negatives If set, all negative values in the result are set to zero.
SOBEL implements an approximation of the 3-by-3 nonlinear edge enhancement operator:
Y = (A0 + 2A1 + A2) - (A6 + 2A5 + A4)
CAUTION: Because the result image is saved in integer format, large original data values will cause overflow. Overflow occurs when the absolute value of the result is larger than 32,767. Use the No_Clip keyword to avoid overflow.
With this information, it is possible to identify and compare features or items in an image with those in another image, usually for verification or detection purposes. SOBEL and other edge-detection algorithms are used extensively for image processing and preprocessing for pattern recognition.
The image returned by SOBEL contains the edges present in the original image, with the brightest edges representing a rapid transition (well-defined features), and darker edges representing smoother transitions (blurred or blended features).
An original image can also be somewhat sharpened by adding or averaging the edge-detected image with the original image.
Figure 2-119 The SOBEL function has been used with this 512-by-512 aerial image to make the edges stand out with sharp contrast.
Figure 2-120 The SOBEL function has been used with this 512-by-512 aerial image to make the edges stand out with sharp contrast.