计算机工程与应用 ›› 2025, Vol. 61 ›› Issue (9): 277-287.DOI: 10.3778/j.issn.1002-8331.2312-0414

• 图形图像处理 • 上一篇    下一篇

结合线稿提示的热贡建筑彩绘图像多路编码上色网络

程苗,张效娟,赵洋,范虹   

  1. 1.青海师范大学 计算机学院,西宁 810016
    2.省部共建藏语智能信息处理及应用国家重点实验室,西宁 810016
    3.合肥工业大学 计算机与信息学院,合肥 230002
    4.陕西师范大学 计算机科学学院,西安 710062
  • 出版日期:2025-05-01 发布日期:2025-04-30

Multiple Encoding Coloring Network for Regong Architectural Colored Drawing Images Combining Sketch Hints

CHENG Miao, ZHANG Xiaojuan, ZHAO Yang, FAN Hong   

  1. 1.School of Computer Science, Qinghai Normal University, Xining 810016, China
    2.State Key Laboratory of Tibetan Intelligent Information Processing and Application, Xining 810016, China
    3.School of Computer and Information, Hefei University of Technology, Hefei 230002, China
    4.School of Computer and Science, Shaanxi Normal University, Xi’an 710062, China
  • Online:2025-05-01 Published:2025-04-30

摘要: 建筑彩绘是人类非物质文化遗产热贡艺术的重要组成部分,一些年代久远存在褪色氧化现象的建筑彩绘因环境因素和传承现状的限制得不到及时的维护,这严重影响热贡建筑彩绘艺术的鉴赏和保护。针对现有的图像上色方法对建筑彩绘图像进行上色时存在的颜色混淆、串色漏色等问题,提出一种端到端的结合线稿提示的热贡建筑彩绘图像多路编码上色网络。该网络以提取的线稿图作为图像先验知识补充特征传递过程中忽视的纹理细节信息,加强网络对全局语义的理解,改善串色漏色的现象;多路并行编码模块以三个空洞卷积和传统卷积不同排列方式的编码分支为结构,通过获得不同尺度的的感受野以此更好地捕捉上下文信息,提高色彩特征的提取能力;结合空间注意力和通道注意力的注意力残差模块,通过对特征信息的重新整合加工,帮助网络全面理解图像色彩特征和纹理信息的空间分布,提高上色质量。所提方法在构建的热贡建筑彩绘数据集和动漫数据集上进行对比实验,与现有上色方法相比,所提方法在定性分析和定量分析中具有较好的表现,在主观评价的对比中也获得与人类主观审美和专业要求最一致的结果。实验证明,所提方法图像上色效果优于其他上色方法,在热贡建筑彩绘图像上色领域具有较大应用价值。

关键词: 热贡建筑彩绘, 图像上色, 多路并行编码, 注意力残差, 线稿提示

Abstract: Architectural colored drawing is an important component of the human intangible cultural heritage of Regong art. Some ancient Regong architectural colored drawings have the phenomenon of fading and oxidation, which cannot be maintained promptly due to environmental factors and the limitations of inheritance status. This seriously affects the appreciation and protection of the Regong architectural colored drawings art. Aiming at the problems of color confusion and color leakage when using existing image coloring methods to color architectural colored drawing images, this thesis proposes an end-to-end multiple encoding coloring network for Regong architectural colored drawing images that combines sketch hints. This network supplements the ignored texture details in the feature transfer process with extracted sketch as prior knowledge of the image, enhances the network’s understanding of global semantics, and improves the phenomenon of color distortion and leakage. The multipath parallel encoding module is structured with three encoding branches arranged in different ways using dilated convolutions and traditional convolutions. By obtaining receptive fields of various scales, it better captures contextual information and improves the ability to extract color features. The attention residual module, which combines spatial attention and channel attention, helps the network comprehensively understand the spatial distribution of image color and texture information through the fusion processing of feature information, thereby improving the quality of coloring. Finally, a comparative experiment is conducted on the constructed Regong architectural colored drawing dataset and animation dataset using the proposed method. Compared with existing coloring methods, the proposed method performs well in qualitative and quantitative analysis and achieves the most consistent results with human subjective aesthetics and professional requirements in subjective evaluation comparison. Experimental results have shown that the proposed method has better image coloring effects than other coloring methods and has significant application value in the field of the coloring of Regong architectural colored drawings art.

Key words: Regong architectural colored drawing, image coloring, multipath parallel encoding, attention residual, sketch hints