一种多阶段的黑白影像智能色彩修复算法

Multi-stage Intelligent Color Restoration Algorithm for Black-and-White Movies

针对黑白电影的上色过程中,自动上色模型只生成一种结果导致上色结果单一、基于参考示例上色方法需要用户指定参考图像、参考图像的高要求会耗费大量人力的问题,提出了一种多阶段的黑白影像智能色彩修复算法(A Multi-Stage Intelligent Color Restoration Algorithm for Black-and-White Movies,MSICRA)。首先,使用VGG19网络将电影分割为多个场景片段;其次,将每个场景片段逐帧切割,将每帧图像的边缘强度和灰度差作为图像清晰度评判指标,筛选出每个场景中清晰度位于[0.95,1]区间的图像;然后,选择筛选出的图像中的第一张,使用不同的渲染因子值进行上色,利用饱和度进行上色效果的评估,选择合适的渲染因子值对筛选出的图像上色;最后,利用上色前和上色后图像之间的均方误差选择上色质量较好的图像作为该场景片段上色的参考图像。实验结果表明,所提算法在黑白电影《雷锋》和《永不消逝的电波》的PSNR上分别提高了1.32%和2.15%,SSIM分别提高了1.84%和1.04%。该算法不仅可以实现全自动上色,而且颜色真实,符合人们的认知。

In the process of colorization for black and white movies,the existing automatic colorization models often produce singular result,and the reference-based colorization methods require users to specify reference images,posing a significant challenge in meeting the high requirement of reference images and consuming substantial human efforts.To address this issue,this paper proposes a multi-stage intelligent color restoration algorithm for black-and-white movies(MSICRA).Firstly,the movie is splitted into multiple scene segments by the VGG19 network.Secondly,each scene segment is cut frame by frame,and the edge intensity and grayscale difference of each frame image are used as criteria to assess image clarity,selecting images with clarity ranging from 0.95 to 1 in each scene.Subsequently,we select the first frame that meets the clarity criteria from the filtered images and apply different render factor values to colorize the selected image.We assess the colorization effects using saturation and choose the appropriate render factor for the colorization.Finally,we use the mean squared error between the pre-colorized and post-colorized images to select the best quality colorized image as the reference for the scene segment.Experimental results demonstrate that the proposed algorithm improves the PSNR by 1.32%for the black and white films Lei Feng and 2.15%for The Eternal Wave,and the SSIM by 1.84%and 1.04%respectively.The algorithm not only enables fully automatic colorization but also produces realistic colors that align with human perception.