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Furthermore, image edge enhancement is performed jointly with this algorithm to save memory cost.
To identify the moving edges from, two edge maps: left difference image edge map and right difference image edge map are computed.
Image edge detection plays an important role in determining the feature boundary points and their moving directions as the basis for extraction of PTGW images Spiral Architecture (SA) has proved efficient for image edge detection.
Moreover, some comparisons are also given to prove that our method outperforms classical operators in gray image edge detection.
Hence, (1) is utilized to generate difference image edge maps instead of utilizing edge differencing approach.
Experimental results indicate that new approach shows superior performance on preserving image edge and curvature geometric structure.
The connection is made between digital image processing, in particular, image edge detection, and numerical shock capturing.
The proposed algorithm can preserve the image edge details and obtain the satisfactory visual effect.
τ → x, y is always orthogonal to the tangent of the image edge.
ν is the distance between the curve and the image edge.
It contains the lowest distance value in the location of the difference image edge maps.
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