A Robust and Universal Gradient Domain Imaging Solver Using Gradient Variables and Locally Varying Metrics
| dc.contributor.author | Neumann, László | en_US |
| dc.contributor.author | Hegedüs, Ramón | en_US |
| dc.contributor.editor | Pauline Jepp and Oliver Deussen | en_US |
| dc.date.accessioned | 2013-10-22T07:18:24Z | |
| dc.date.available | 2013-10-22T07:18:24Z | |
| dc.date.issued | 2010 | en_US |
| dc.description.abstract | Gradient Domain Imaging (GDI) has gained a high importance and provoked numerous powerful applications over the last decade. It employs a workflow of creating an inconsistent gradient field (GF) from one or more images using different non-linear operations and finally it determines an image with a consistent, integrable GF that falls near to the prescribed inconsistent one. However, the result is not really predictable, often suffers from halo-effects and other local distortions at higher frequencies as well as from uncontrollable far-effects arising from local gradient-contradictions. The unfolding of these artifacts culminates in an undesired overall image appearance. None of the common GDI solvers can overcome these side-effects as they utilize the same local isotropic 'coefficient-pattern' in a sparse matrix description and they differ only in the numerical solution techniques. We present a powerful GDI method solving the problem completely in the gradient domain with gradient-variables and using spatially varying metrics that depends only on the starting inconsistent gradient field. After obtaining the nearest consistent gradient field with the pre-defined metrics we return into the image space by double integration that yields the wanted pixel intensity values. Our method delivers a great aesthetic enhancement by eliminating halo effects and saving small details, furthermore providing a realistic and pleasant overall light distribution at lower frequencies. By significantly extending the range of allowed inconsistency in the prescribed gradient field, it also allows for solving a large class of problems that proved hopeless beforehand. | en_US |
| dc.description.seriesinformation | Computational Aesthetics in Graphics, Visualization, and Imaging | en_US |
| dc.identifier.isbn | 978-3-905674-24-8 | en_US |
| dc.identifier.issn | 1816-0859 | en_US |
| dc.identifier.uri | https://doi.org/10.2312/COMPAESTH/COMPAESTH10/017-024 | en_US |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture/Image Generation-Display algorithms | en_US |
| dc.title | A Robust and Universal Gradient Domain Imaging Solver Using Gradient Variables and Locally Varying Metrics | en_US |
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