首页|面向建筑彩绘纹样的高质量贴图重构方法

面向建筑彩绘纹样的高质量贴图重构方法

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建筑彩绘是绘制在木构建筑上的精美图案.在古建筑进行数字化展示时,通用处理方法是以网格模型加单张纹理的模式进行绘制.由于单张纹理贴图分辨率有限,无法展示所有细节,且常见的纹理为位图格式,使用多张高分辨率贴图会导致显存占用过大,致使数据交换效率变低.为解决上述难题,提出了一种高质量贴图重构方法.利用彩绘图案的自相似性和对称性,提取彩绘纹样最小不重复单元及版式信息.使用矢量数据表示最小图元并构建纹样素材库.在编辑三维模型的彩绘纹案时,通过复用图元并配置相应变换参数编码生成描述性文件,用以完成彩绘内容的渲染.实验结果表明,该方法有效减少了重复信息的存储,且提供更为清晰的细节,更好地进行数字化展示.
High-quality texture reconstruction method for architectural painted patterns
Architectural painted patterns refer to the exquisite patterns painted on wooden structures.When digitizing ancient architecture,the general solution involves using a mesh combined with a single texture map for rendering.However,due to the limited resolution of a single texture map,not all details can be adequately displayed.Moreover,common textures are stored pixel by pixel,and using multiple high-resolution texture maps can lead to excessive graphics processing unit memory usage,resulting in lower data exchange efficiency.To address the aforementioned challenges,a method for high-quality texture map reconstruction was proposed.This method employed the self-similarity and symmetry of the painted patterns,thereby extracting the smallest unduplicated pattern elements and layout information of the painted patterns.Vectorized data was utilized to represent the smallest pattern elements,and a library of pattern elements was constructed.When editing the painted patterns of a 3D model,these pattern elements were reused and configured with corresponding transformation parameters,which were encoded into descriptive files to complete the rendering of the painted content.Experimental results demonstrated that the proposed method could effectively reduce the storage of redundant information and provide a better presentation of details,thus enhancing realistic rendering.

realistic renderingimage vectorization representationlayout structuretexture compressionarchitectural painted patterns

龚辰晨、曹力、张腾腾、吴奕泽

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合肥工业大学计算机与信息学院(人工智能学院),安徽 合肥 230009

合肥工业大学安全关键工业测控技术教育部工程研究中心,安徽 合肥 230009

真实感绘制 图像矢量化表达 版式结构 纹理压缩 建筑彩绘纹样

国家自然科学基金项目国家自然科学基金项目安徽省重点研究与开发项目青海省科技转化项目

6160214662272142202104e110200062022-QY-203

2024

10.11996/JG.j.2095-302X.2024040804

图学学报
中国图学学会

图学学报

CSTPCD北大核心
影响因子：0.73
ISSN：2095-302X
年,卷(期)：2024.45(4)