Gradient-___domain image processing: Difference between revisions

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'''Gradient -___domain image processing''' is a relatively new type of [[digital image processing]] that operates on the differences between neighboring pixels, rather than on the pixel values directly. An [[image gradient]] represents the derivative of an image, so gradient -___domain processing involves solving an integral to extract an image from the gradient, which requires solving [[Poisson's equation]]. <ref name="Bhat2010">Bhat, Pravin, et al. "Gradientshop: A gradient-___domain optimization framework for image and video filtering." ACM Transactions on Graphics (TOG) 29.2 (2010): 10.</ref>

== Basics ==

Processing images in the gradient ___domain is a two-step process. The first step is to obtainchoose an image gradient. This is often extracted from an existing image and then modified, but it can be createdobtained through anyother means as well. SomeFor example, some researchers have explored the advantages of users painting directly in the gradient -___domain.<ref>McCann, James, and Nancy S. Pollard. "Real-time gradient-___domain painting." ACM Transactions on Graphics (TOG). Vol. 27. No. 3. ACM, 2008.</ref> The nextsecond step is to solve Poisson's equation to find a new image that producescan produce the desired gradient from the first step. An exact solution is often not possible so an image is found that approximates the desired gradient as closely as possible.

== 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>

* seamless [[image stitching]]

* combining photographs of the same scene but with different lighting and exposure into one image

* removal of unwanted details from an image<ref name="Perez2003">Pérez, Patrick, Michel Gangnet, and Andrew Blake. "Poisson image editing." ACM Transactions on Graphics (TOG). Vol. 22. No. 3. ACM, 2003.</ref>

* [[non-photorealistic rendering]] filters<ref name="Bhat2010" />

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

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