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An efficient projection defocus algorithm based on multi-scale convolution kernel templates

机译:一种基于多尺度卷积核模板的高效投影散焦算法

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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.
机译:投影的焦点问题包括由于机械聚焦不完全和投影像素化所产生的屏幕门效应而导致的投影机的散焦投影图像。为了消除这些缺陷,提高投影仪的成像质量和清晰度,提出了一种基于多尺度卷积核模板的自适应投影散焦算法。该算法应用改进的Sobel-Tenengrad聚焦评估函数来计算强度均衡的清晰度,然后构造多尺度散焦卷积核以重新映射和渲染散焦投影图像。由此产生的投影散焦校正图像可以消除散焦效果,并提高未校正图像的清晰度。实验表明,该算法可以快速,强大地运行,不仅可以有效消除视觉伪影,并且可以在自行设计的智能投影系统上实时运行,而且还可以显着提高观察者的视觉分辨率和清晰度。

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