630 research outputs found
Image Completion for View Synthesis Using Markov Random Fields and Efficient Belief Propagation
View synthesis is a process for generating novel views from a scene which has
been recorded with a 3-D camera setup. It has important applications in 3-D
post-production and 2-D to 3-D conversion. However, a central problem in the
generation of novel views lies in the handling of disocclusions. Background
content, which was occluded in the original view, may become unveiled in the
synthesized view. This leads to missing information in the generated view which
has to be filled in a visually plausible manner. We present an inpainting
algorithm for disocclusion filling in synthesized views based on Markov random
fields and efficient belief propagation. We compare the result to two
state-of-the-art algorithms and demonstrate a significant improvement in image
quality.Comment: Published version:
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=673843
Image Inpainting by Hyperbolic Selection of Pixels for Two Dimensional Bicubic Interpolations
Image inpainting is a restoration process which has numerous applications.
Restoring of scanned old images with scratches, or removing objects in images
are some of inpainting applications. Different approaches have been used for
implementation of inpainting algorithms. Interpolation approaches only consider
one direction for this purpose. In this paper we present a new perspective to
image inpainting. We consider multiple directions and apply both
one-dimensional and two-dimensional bicubic interpolations. Neighboring pixels
are selected in a hyperbolic formation to better preserve corner pixels. We
compare our work with recent inpainting approaches to show our superior
results
Digital image processing of the Ghent altarpiece : supporting the painting's study and conservation treatment
In this article, we show progress in certain image processing
techniques that can support the physical restoration of the painting, its art-historical analysis, or both. We show how analysis of the crack patterns could indicate possible areas of overpaint, which may be of great value for the physical restoration campaign, after further validation. Next, we explore how digital image inpainting can serve as a simulation for the restoration of paint losses. Finally, we explore how the statistical analysis of the relatively simple and frequently recurring objects (such as pearls in this masterpiece) may characterize the consistency of the painter’s style and thereby aid both art-historical interpretation and physical restoration campaign
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