Gradient-___domain image processing: Difference between revisions

Revision as of 01:47, 8 August 2014

Revision as of 01:49, 8 August 2014

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== Image Processing ==

For image processing purposes, the gradient is obtained from an existing image and modified. Various methods, such as a [[Sobel]] operator]], can be used to find the gradient of a given image. This gradient can then be manipulated directly to achieve a number of different effects when the resulting image is solved for. For example, if the gradient is scaled by a uniform constant it results in a simple sharpening filter. A better sharpening filter can be made by only scaling the gradient in areas deemed important.<ref name="Bhat2010" />

Other uses include:

* seamless [[image stitching]]<ref>Levin, Anat, et al. "Seamless image stitching in the gradient ___domain." Computer Vision-ECCV 2004. Springer Berlin Heidelberg, 2004. 377-389.</ref>

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* image [[deblocking]]<ref name="Bhat2010" />

* the ability to seamlessly clone one part of an image onto another in ways that are difficult to achieve with conventional image ___domain techniques.<ref name="Perez2003" />

==References==