Paper Info
Title
Edge enhancement of depth based rendered images
Abstract
Depth image based rendering is a well-known technology for the generation of virtual views in between a limited set of views acquired by a cameras array. Intermediate views are rendered by warping image pixels based on their depth. Nonetheless, depth maps are usually imperfect as they need to be estimated through stereo matching algorithms; moreover, for representation and transmission requirements depth values are obviously quantized. Such depth representation errors translate into a warping error when generating intermediate views thus impacting on the rendered image quality. We observe that depth errors turn to be very critical when they affect the object contours since in such a case they cause significant structural distortion in the warped objects. This paper presents an algorithm to improve the visual quality of the synthesized views by enforcing the shape of the edges in presence of erroneous depth estimates. We show that it is possible to significantly improve the visual quality of the interpolated view by enforcing prior knowledge on the admissible deformations of edges under projective transformation. Both visual and objective results show that the proposed approach is very effective.
Year
DOI
Venue
2014
10.1109/ICIP.2014.7026103
Image Processing
Keywords
Field
DocType
image enhancement,image texture,rendering (computer graphics),admissible deformations,depth errors,depth image based rendering,edge enhancement,erroneous depth estimation,image quality,object contours,projective transformation,structural distortion,visual quality,warped objects,3DTV,View synthesis,depth image based rendering,quality enhancement
Computer vision,Image warping,Pattern recognition,Computer science,Image quality,View synthesis,Homography,Artificial intelligence,Depth map,Image-based modeling and rendering,Rendering (computer graphics),Edge enhancement
Conference
ISSN
Citations 
PageRank 
1522-4880
2
0.36
References 
Authors
7
3
Name
Order
Citations
PageRank
Muhammad Shahid Farid1519.40
M. Lucenteforte28712.89
Marco Grangetto345642.27