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Film Colorization, Using Artificial Neural Networks and Laws Filters

机译:胶片着色,使用人工神经网络和法律过滤器

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—In this study a new artificial neural network based approach to automatic or semi-automatic colorization of black and white film footages is introduced. Different features of black and white images are tried as the input of a MLP neural network which has been trained to colorize the movie using its first frame as the ground truth. Amongst the features tried, e.g. position, relaxed position, luminance, and so on, we are most interested on the texture features namely the Laws filter responses, and what their performance would be in the process of colorization. Also, the network parameter optimization, the effects of color reduction, and relaxed x-y position of pixels as the feature, are investigated in this study. The results are promising and show that the combination of MLP and texture features is effective in this application.
机译:- 本研究了一种新的人工神经网络基于自动或半自动着色的黑白胶片镜片的方法。黑白图像的不同特征被尝试为MLP神经网络的输入,该信息已被培训以使用其第一帧作为地面真理将电影着色。在尝试的功能中,例如,位置,轻松的位置,亮度等,我们对纹理最感兴趣的是法律滤波器响应,以及它们的性能在着色过程中。此外,在本研究中研究了网络参数优化,颜色减少的效果和像素的宽松X-Y位置,在本研究中研究了该特征。结果是有前途的,并且表明MLP和纹理特征的组合在本申请中是有效的。

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