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摘要:
颜色传递是近年来图像处理和计算机视觉领域的热门研究问题，随着立体图像技术的发展，对于立体图像的颜色传递越来越受关注。本文提出一种双目立体图像的颜色传递方法，在完成颜色传递的同时力求提升用户的观看体验。根据用户实际需求，可以对目标对象进行颜色传递，而保持背景的颜色不改变。在本文提出的方法中，由用户指定图像对象，然后用图割的方法进行图像分割，根据所选对象与目标图像颜色特征的多元高斯模型匹配完成颜色传递。为了进一步增强观看效果，本文在颜色传递的同时进行非线性视差优化，从而提高目标对象的深度感。本文从不同立体图像库中随机选取图像进行实验，实验结果表明，本文方法中颜色传递和视差优化的结合，可以很好地提升立体图像的观看体验。
Abstract:Color transfer has been a hot research issue in the field of image processing and computer vision in recent years. The main purpose is to transfer the color of a target image to source image so that the source image has the same or similar color features with the target image. In practical applications for the color transfer of binocular stereoscopic images, the user may only need to transfer the color of the selected object while keeping the background color unchanged. For this purpose, a color transfer method based on the selected object is proposed in this paper. In the method, by assigning the object of the image by user, the accurate object is segmented via graph cut, and the probability density curves of color distribution between the selected object and the target image are matched to accomplish the color transfer. In order to enhance the viewing experience provided for the user, a non-linear disparity optimization is performed after the color transfer operation. According to the histogram feature of disparity map, the disparity mapping function is calculated, and the target disparity is obtained to enhance the depth sensation of the selected object. The experimental results demonstrate that the combination of stereoscopic color transfer and disparity remapping effectively enhances the stereoscopic viewing experience.
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Overview: Color transfer is a hot research topic in the field of image processing and machine vision in recent years. It is a process of transferring the color of a target image to the source image so that the source image and the target image have the same or similar color characteristics. It has a wide range of application prospects and can be used for image color correction, re-rendering and artistic processing. The existing color transfer methods are to process only the 2D image, establish the source image and the target image color feature multivariate Gaussian model by parameter estimation, and get the source image color feature model by multivariate Gaussian function transformation to approach the color feature model of the target image, then finish the color transfer. With the development of stereoscopic image technology, the color transfer of stereoscopic images has attracted more and more attention. In this paper, a color transfer strategy for binocular stereoscopic images is proposed, which can improve the viewing experience of users while completing color transfer. According to the actual needs of users, we can only transfer the color of the target object, and keep the color of the background unchanged. In the proposed method, the user specifies the image object, and then uses the graph cut method to segment the image, according to the selected object and the color feature model matching of the target image to complete color transfer. In order to further enhance the viewing effect, this paper carries out nonlinear disparity optimization while color transfer, so as to improve the depth of the object. According to the histogram feature of disparity map, the region which has a great influence on the stereoscopic image is determined, and the disparity mapping function is calculated by integral operation, then the disparity of the selected object which makes the depth sense of the selected object more intense is obtained. In this paper, images are randomly selected from different stereo image databases and our experiment results have been compared with the linear disparity adjustment method. The results show that this method can improve the depth sense of the object more effectively. To prove the effect of this strategy, a subjective experiment is designed, in which different people are demanded to wear stereo glasses to choose the images they feel better. Experimental results show that the combination of color transfer and disparity optimization can effectively improve the viewing experience of stereoscopic images.
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