Grayscaleimage coloring method based on reference image color style

Abstract

The invention discloses a grayscale image coloring method based on a reference image color style. The grayscale image coloring method can be used as a solution for the problems of line draft coloring and black-and-white image coloring. The specific implementation of the method comprises the following steps: 1, drawing up a coloring image category library, collecting a color image data set according to categories, carrying out line draft extraction or graying on the color image data set, and extracting color histogram information of the color image data set; 2, taking the color image, the line draft or the gray level image and the color histogram information as a training set, inputting the training set into the network for training, and obtaining a coloring model corresponding to the category; and 3, re-inputting the image to be colored into the network, and coloring the image by using the model obtained in the step 2; and 4, evaluating a coloring result. The grayscale image coloring method based on the reference image color style can solve the coloring problem of various types of line manuscripts and black-and-white images, and it is proved that the coloring effect is good in practice.

Description

technical field [0001] The invention belongs to the field of computer technology and image processing, in particular to a grayscale image coloring method based on the color style of a reference image. Background technique [0002] Image coloring is to restore and enhance the expressive effect of the original image, improve its visual experience, enrich the semantics of the image, and increase its application value. As early as the 19th century, it was popular to restore black and white photos by manual coloring. With the development of technology, image coloring has been widely used in film and television processing, animation art and other fields. For example, in the comics industry, the use of image coloring technology can solve the time-consuming and labor-intensive problems of coloring a large number of black and white line drafts, saving drawing costs without affecting the reading experience of buyers; in the film industry, the viewing experience of early black and whit...

AI Technical Summary

Problems solved by technology

Although the application of convolutional neural network is still a relatively mainstream method, it still has the problem of complex loss function design. In the face of diverse image coloring requirements, different loss functions need to be artificially designed, otherwise it is easy to produce Issues with ambiguous results, etc.

Images