中国古代的绞经织物独树一帜，风格鲜明，在漫长的发展历史中，绞经织物发展出了多样性的组织结构，经历了几次重大的变革与转型。以罗为代表，其组织结构的发展与当时历史环境下的社会发展和技术演变息息相关。综合来看，经纱的绞缠部分令绞经织物的组织结构格外复杂，使得绞经织机及其织造技艺具有了独特的技术内容，因其织造难度大，受到诸多因素影响而产生破损、难以提取等因素，古代多样化的绞经织造技艺到了现代只得到了小部分的传承。所以，无论是古代绞经织物本身承载的技术与社会人文内涵，还是其技艺在现代的传承与发展方面，都还有很大的研究空间。本课题以宋代四经绞罗的纹样为研究对象，以修复纹样并使用在现代设计中为切入点，以探寻其创新应用的可能性为目的，对其纹样种类、纹样特征、文化内涵等内容进行研究，希望能够增强人们对于绞罗这类丝织物的保护意识，让更多人了解其魅力。主要研究内容如下：

（1）对绞经织物的研究背景和意义进行探讨。通过对史书与论著的查阅，探究其所含有的艺术特征以及蕴含的文化内涵。同时，整理出调研的国内外数字化修复方法，结合自身研究的需要对其进行梳理归纳，提出本课题所使用的方法，并调研文化创意设计与设计元素创新方法，探索出一条属于四经绞罗纹样再利用的创新流程。

（2）论述了绞经织物的历史溯源和分类，得出其中最具有代表性的四经绞罗，探讨了在历史发展过程中四经绞罗的织造技术及传承特点，归纳出宋代四经绞罗的独特织造手法，并总结了宋代四经绞罗纹样的种类与特征。

（3）基于Criminisi算法对四经绞罗的纹样进行修复，提出一种结合开运算和Criminisi算法的图像修复方法。收集具有规律型特征的四经绞罗传统纹样，用图谱分析法分析，使用原算法和开运算改进过的Criminisi算法进行修复。对图像进行剪裁、得出掩膜、计算优先权、最后进行纹样填充。分别完成了四经绞罗规律型图样的数字化修复。实验结果表明，经过开运算改进的Criminisi算法弥补了原算法的不足，修复后的图像和原算法修复的相比更加清晰平滑，有助于运用在之后的纹样设计中，验证了此算法修复四经绞罗纹样的可行性与可信性，为罗织物的传承和发展提供新的思路。

（4）归纳出四经绞罗传承的局限性，结合现有设计实例分析传统文化元素在现代社会中运用的现状，提出四经绞罗纹样在现代设计切实可行的创新方法，分析总结出四经绞罗设计元素应用的基本原则。并综合前文对其美学特征及文化内涵的研究，以期实现四经绞罗的代表纹样特征的传承，并为传统文化元素的传承与创新提供新的思路。

The warp fabric in ancient China has its own school and distinctive style. In the long history of development, the warp fabric has developed a variety of organizational structures and experienced several significant changes and transformations. Taking Luo as the representative, the development of its organizational structure was closely related to the social development and technological evolution under the historical environment at that time. Generally speaking, the twisting part of warp yarn makes the organization structure of warp fabric extremely complicated, which makes warp loom and weaving technique have unique technical content. Due to its difficulty in weaving, it is damaged and difficult to extract due to the influence of many factors, etc., the diversified warp weaving technique in ancient times has only been a small part of the inheritance in modern times. Therefore, there is still a lot of research space for both the technical and social cultural connotation carried by ancient twisted fabric itself and the inheritance and development of its skills in modern times. This subject takes the patterns of the four classic strands of the Song Dynasty as the research object, takes the restoration of the patterns and their use in modern design as the entry point, and aims to explore the possibility of their innovative application. It studies the types, features and cultural connotations of the patterns, hoping to enhance people's awareness of the protection of this kind of silk fabric, and let more people understand its charm. The main research contents are as follows:

(1) The research background and significance of twisted fabric are discussed. Through consulting the historical books and treatises, we explore the artistic features and cultural connotations contained in them. At the same time, I sorted out the digital restoration methods at home and abroad, sorted out and summarized them in combination with the needs of my own research, put forward the method used in this topic, investigated the creative cultural design and design element innovation methods, and explored an innovative process belonging to the reuse of four warp twisted patterns.

(2) This paper discusses the historical origin and classification of warp warp fabric, obtains the most representative four-warp twist, discusses the weaving technology and inheritance characteristics of the four-warp twist in the historical development process, summarizes the unique weaving techniques of the four-warp twist in the Song Dynasty, and summarizes the types and characteristics of the patterns of the four-warp twist in the Song Dynasty.

(3) Based on Criminisi algorithm, Criminisi should be used to repair four-warp crimping patterns, and a Criminisi image repair method combined with open operation and Criminisi algorithm is proposed. The traditional patterns of four-way twisted romp with regular characteristics should be collected and analyzed by atlas analysis method. The original algorithm and the improved Criminisi algorithm should be used to repair criminisi. The image is clipped, the mask is obtained, the priority is calculated, and finally the pattern is filled. The digital restoration of the regular pattern of four strands was completed respectively. The experimental results show that the Criminisi algorithm improved after opening operation makes up for the shortcomings of the original algorithm. Compared with the original algorithm, the repaired image is clearer and smoother, which is conducive to the application in the future pattern design, verifies the feasibility and credibility of the algorithm in repairing the four-way twisted yarn pattern, and provides a new idea for the inheritance and development of Luo fabric.

(4) Summed up the limitations of four-warp twist inheritance, combined with the existing design examples to analyze the application of traditional cultural elements in modern society, put forward the feasible innovative method of four-warp twist pattern in modern design, analyzed and summarized the basic principles of the application of four-warp twist design elements. Based on the above studies on its aesthetic characteristics and cultural connotation, this paper aims to realize the inheritance of the representative pattern characteristics of the four-warp twisted, and provide new ideas for the inheritance and innovation of traditional cultural elements.

[1]柳宗悦.工艺文化[M].徐艺乙,译.桂林:广西师范大学出版社,2006.

[2]王国英.习近平新时代中国特色社会主义思想关键概念研究[D].上海:华东师范大学,2022.

[3]《国家“十一五”时期文化发展规划纲要》摘要[J].广告人,2008(02):165.

[4]国家“十二五”时期文化改革发展规划纲要[J].青年记者,2012,No.375(07):50.

[5]沈传亮.准确认识党的十八届三中全会的划时代地位[N].经济日报,2019-02-11(012).

[2]袁源,吴智慧.留住手艺-工业时代的手工业[J]装饰,2005(03):18-19.

[7]金元浦.我国当前文化创意产业发展的新形态、新趋势与新问题[J]中国人民大学学报,2016.30(04):2-10.

[8]尹定邦.邵宏.设计学概论[M].长沙:湖南科学技术出版社,2016:530.

[9]本雅明.机械复制时代的艺术作品[M].王才勇,译北京:中国城市出版社,2002.

[10]庄琦.基于DCGAN的缺损图像修复算法研究[D].内蒙古科技大学,2022.

[11]ANTONIO C, PATRICK P, KENTARO T. Region filling and object removal by exemplar-based image inpainting [J]. IEEE transactions on image processing: a publication of the IEEE Signal Processing Society,2004,13(9):1200-1212.

[12]李英,杨秋翔,雷海卫,等.基于深度图像绘制技术的Criminisi算法的改进[J].计 算机工程与设计,2017,38(05):1287-1291.

[13]何雨亭,唐向宏,张越,等.结构张量的改进Criminisi修复[J].中国图象图形学 报,2018,23(10):1492-1507.

[14]Bertalmio M, Sapiro G, Caselles V, et al. Image Inpainting[C]// SIGGRAPH conference,2000:417-424.

[15]Jun J, Zhao-Xia W. The research of Tibet mural digital images inpainting using CDD model[C]// 2013 2nd International Symposium on Instrumentation & Measurement, Sensor Network and Automation (IMSNA). IEEE, 2013:805-807.

[16]Fadili J M, Starck J L. EM Algorithm for Sparse Representation-based Image Inpainting[C]// IEEE International Conference on Image Processing. IEEE,2005:11-61.

[17]Bai H, Li X, Jiang Q, et al. On optimal sparsifying dictionary design with application to image inpainting[C] IEEE International Conference on Digital Signal Processing.IEEE,2015:361-365.

[18]CAI T T, ZHANG A. Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-Rank Matrices [J]. IEEE Transactions on Information Theory, 2014, 60(1):122-132.

[19]张倩侃,计忠平,付晓峰.二次联合稀疏表示和低秩近似的浅浮雕优化[J].中国 图象图形学报,2020,25(06):1245-1259.

[20] LU X, WANG Y, YUAN Y. Graph-Regularized Low-Rank Representation for Destriping of Hyperspectral Images [J]. IEEE Transactions on Geoscience and Remote Sensing,2013,51(7):4009-4018.

[21] BABACAN S D, LUESSI M, MOLINA R, et al. Sparse Bayesian Methods for

Low-Rank Matrix Estimation [J]. IEEE Transactions on Signal Processing, 2012, 60(8): 3964-3977.

[22]Zhou M, Wang C, Chen M, et al. Nonparametric Bayesian matrix completion[C]// 2010 IEEE Sensor Array and Multichannel Signal Processing Workshop. IEEE,2010: 213-216.

[23]PARKER J T, SCHNITER P, CEVHER V. Bilinear Generalized Approximate Message Passing—Part I: Derivation [J]. IEEE Transactions on Signal Processing, 2014,62(22):5839-5853.

[24]PARKER, JASON T, SCHNITER, et al. Bilinear Generalized Approximate Message Passing-Part II: Applications [J]. IEEE Transactions on Signal Processing: A publication of the IEEE Signal Processing Society,2014,62(22):5854-5867.

[25]WANG, YIZHOU, XIN, et al. Exploring Algorithmic Limits of Matrix Rank Minimization Under Affine Constraints [J]. IEEE Transactions on Signal Processing A Publication of the IEEE Signal Processing Society,2016,64(19):4960-4974.

[26]PATHAK D, KRAHENBUHL P, DONAHUE J, et al. Context Encoders: Feature Learning by Inpainting [J]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016:2536-2544.

[27]Iizuka S, Simo-Serra E, Ishikawa H. Globally and locally consistent image completion[J]. ACM Transactions on Graphics,2017,36(4):1-14.

[28]陈雅忱,罗锦烨.全球非物质文化遗产保护制度演进路径[J].经济地理,2022,42(06):225-230.

[29]孔紫剑.基于视觉特性与图像特征的图像质量评价[D].云南:云南大学,2021.

[30]庞芳.视觉传达设计中视觉思维模式的创新路径[J].艺术品鉴,2022(26):73-76.

[31]王子琪.中国古代绞经织物结构、技艺与文化研究[D].上海:东华大学,2021.

[32]南京博物馆.文物资料丛刊3，江苏吴县草鞋山遗址[D].北京:文物出版社，1978.

[33]蔡陛霞,荆妙蕾.修订.织物结构与设计[M].北京:中国纺织出版社2004.

[34]南京博物院:《江苏吴县草鞋山遗址》,《文物资料丛刊》第3辑,北京:文物出版社, 1980.

[35]郑州市文物考古研究所.荥阳青台遗址出土纺织品的报告[J].中原文物, 1999(3).

[36]中国社会科学院考古研究所.殷墟妇好墓[M].北京:文物出版社, 1980.

[37]高汉玉,王任曹,陈云昌.台西村商代遗址出土的纺织品[J].文物,1979(6):44-48.

[38]湖北省.江陵马山一号楚墓[M].北京:文物出版社, 1985.

[39]陈国安,冯玉辉.衡阳县何家皂北宋墓[J].文物, 1984(12):73-76.

[40]陈晶,陈丽华.江苏武进村前南宋墓清理纪要[J].考古, 1986(3):247-260.

[41]福建省博物馆.福州南宋黄升墓[M].北京:文物出版社, 1982.

[42]镇江市博物馆等.金坛南宋周瑀墓[J].考古学报, 1977(1):105-131.

[43]周迪人.德安南宋周氏墓[M].南昌:江西人民出版社, 1999.

[44]杭航,王亚蓉.中国古代纱罗织物品种体系及演变规律[J].丝绸,2022,59(12):126 -135.

[45]湖北省.江陵马山一号楚墓[M].北京:文物出版社, 1985.

[46]杭航,朱立群,李笑苏.明吴氏墓压金云霞翟纹霞帔织物的复制与实践[J].东方收藏,2020(07):106-109.

[47]上海市纺织科学研究院文物研究组.长沙马王堆一号汉墓出土纺织品的研究[M].北京:文物出版社, 1980:29.

[48]罗群.古代提花四经绞罗生产工艺探秘[J].文物保护与考古科学,2008(02):20-26+76-78.

[49]朱霞.基于纹理合成的数字图像和视频修复研究[D].湖南:中南大学,2008.

[50]WEIL Y,LEVOY M.Fast texture synthesis using tree-structured vector quantization [J]. Computer Graphics (Proceedings of SIGGRAPH '00),2000:479-488.

[51]董朋朋.纹理合成技术的研究[D].安徽:中国科学技术大学, 2005.

[52]李雷刚.基于Criminisi的图像修复新方法研究[D].宁夏:北方民族大学,2020.

[53]任澍,唐向宏,康佳伦.纹理和边缘特征相结合的图像修复算法[J].计算机辅助设计与图形学学报,2013,25(11):1682-1693.

[54]路志英,周庆霞,李鑫.基于改进Criminisi算法的地基云图修复方法[J].数据采集与处理,2019,34(1):12-21.

[55]马金秀,张缓缓,景军锋等.基于Criminisi算法的非周期性印花织物缺陷检测[J].纺织高校基础科学学报,2021,34(1):55-60.

[56]刘义成.基于改进Criminisi算法的云南壁画修复研究[D].云南:云南大学,2017.

[57]王琛,闵永军,张天慈.基于改进Criminisi算法的自动驾驶仿真道路场景图像修复[J].软件工程,2022,25(03):44-47.

[58]白瑜.数学形态学与形态学图象处理[J].中国高新技术企业,2008(15):113.

[59]钱月.基于MATLAB的图像形态学处理技术与应用[J].内江师范学院学报,2019,34(10):51-55.

[60]陈尹刚.基于数学形态学图像处理算法研究[J].信息通信,2019(12):67-68.

[61]孙斐.秦绣抽象几何纹样提取与设计应用[J].包装工程,2019,40(16):77-82+107.

[62]谭莹.两宋时期青瓷花莲纹样的艺术特征与演变规律[J].兰台世界,2015(3):144 -145.

[63]田金沙.基于人眼视觉特性的图像质量评价方法研究[D].四川:西南科技大 学,2016.

[64]罗宇豪.结合视觉显著性的图像质量评价方法研究[D].陕西:西安电子科技大 学,2017.

[65]赵雪青.降质图像复原方法研究[D].陕西:陕西师范大学, 2013.

[66]张如画,仝柯,陈晨,论图形视觉语言的功能表现[J]纺织报告,2020,39(09);75-76

[67]周飞.论中国传统吉祥图案的现代设计价值[J].装饰.2007.(03):105

[68]张学文.联想设计法[J].景德镇陶瓷,1991(01):18-24.

[69]陈金亮,赵锋.产品感性意象设计研究进展[J].包装工程,2021,42(20):178-187.