Paper Info
Title
An efficient projection defocus algorithm based on multi-scale convolution kernel templates
Abstract
The focal problems of projection include out-of-focus projection images from the projector caused by incomplete mechanical focus and screen-door effects produced by projection pixilation. To eliminate these defects and enhance the imaging quality and clarity of projectors, a novel adaptive projection defocus algorithm is proposed based on multi-scale convolution kernel templates. This algorithm applies the improved Sobel-Tenengrad focus evaluation function to calculate the sharpness degree of intensity equalization and then constructs multi-scale defocus convolution kernels to remap and render the defocus projection image. The resulting projection defocus corrected images can eliminate out-of-focus effects and improve the sharpness of uncorrected images. Experiments show that the algorithm works quickly and robustly and that it not only effectively eliminates visual artifacts and can run on a self-designed smart projection system in real time but also significantly improves the resolution and clarity of the observer's visual perception.
Year
DOI
Venue
2013
10.1631/jzus.C1300080
Journal of Zhejiang University: Science C
Keywords
Field
DocType
projection focal,projector defocus,multi-scale convolution kernels,sobel-tenengrad evaluation function,Projection focal,Sobel-Tenengrad evaluation function,Projector defocus,Multi-scale convolution kernels,TP391
Visual artifact,Equalization (audio),Computer science,Artificial intelligence,Kernel (image processing),Visual perception,Computer vision,Mathematical optimization,Convolution,Evaluation function,Algorithm,Projector,Observer (quantum physics)
Journal
Volume
Issue
ISSN
14
12
1869196X
Citations 
PageRank 
References 
0
0.34
15
Authors
4
Name
Order
Citations
PageRank
Bo Zhu100.34
Lijun Xie2244.56
Guang-hua Song3564.79
Yao Zheng427629.32