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An efficient projection defocus algorithm based on multi-scale convolution kernel templates
  • 时间:0
  • 分类:TP391.41[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术] O175.5[理学—数学;理学—基础数学]
  • 作者机构:[1]School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027, China, [2]Center for Engineering and Scientific Computation, Zhejiang University, Hangzhou 310027, China
  • 相关基金:Project supported by the National Natural Science Foundation of China (Nos. 11272285, 61008048, and 10876036), the Zhcjiang Provincial Natural Science Foundation (No. LY12F02026), and the Department of Science and Technology of Zhcjiang Province (No. 2009C31112), China
中文摘要:

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.

英文摘要:

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.

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