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图像彩色化方法研究进展
引用本文:马贺贺,周岳斌,饶刚.图像彩色化方法研究进展[J].包装工程,2019,40(3):229-236.
作者姓名:马贺贺  周岳斌  饶刚
作者单位:武汉科技大学机械自动化学院,武汉,430081;湖北文理学院机械工程学院,襄阳,441053
基金项目:湖北省自然科学基金(2015CFC802);“机电汽车”湖北省优势特色学科群开放课题项目(XKQ2017004)
摘    要:目的介绍典型图像彩色化的实现方法及其原理,总结分析图像彩色化方法的特点和应用场景,结合最新研究进展,提出图像彩色化技术以后的研究方向和发展趋势。方法按照图像彩色化技术实现手段分类,对国内外图像彩色化技术研究领域的相关方法进行系统介绍,对比分析基于偏微分方程、图像融合、图像分割的图像彩色化方法及其特点。结论在将来的研究工作中,将图像彩色化技术与其他学科结合,利用计算机的快速处理能力、硬件优势以及丰富的软件资源,并根据应用场景和算法特点,选择合适的图像彩色化方法,可以更好地提高图像处理效率和视觉效果,实现图像彩色化的精准应用。

关 键 词:彩色化  偏微分方程  图像融合  图像分割  红外图像  稀疏表示
收稿时间:2018/5/29 0:00:00
修稿时间:2019/2/10 0:00:00

Research Progress of Image Colorization Methods
MA He-he,ZHOU Yue-bin and RAO Gang.Research Progress of Image Colorization Methods[J].Packaging Engineering,2019,40(3):229-236.
Authors:MA He-he  ZHOU Yue-bin and RAO Gang
Affiliation:1.College of Mechanical Automation, Wuhan University of Science and Technology, Wanhan 430081, China,2.School of Mechanical Engineering, Hubei University of Arts and Science, Xiangyang 441053, China and 1.College of Mechanical Automation, Wuhan University of Science and Technology, Wanhan 430081, China
Abstract:The work aims to introduce the realization method and principle of typical image colorization, summarize and analyze the characteristics and application scenarios of image colorization method, and put forward the research direction and development trend of image colorization technology in the future based on the latest research progress. According to the classification of image colorization technology, the relevant methods in the research field of image colorization technology at home and abroad were systematically introduced, and the image colorization method and its characteristics based on partial differential equation, image fusion and image segmentation were compared and analyzed. In future research work, combining the image colorization technology with other disciplines, using computer rapid processing capability, hardware advantages and rich software resources, and selecting the appropriate image colorization method according to the application scene and algorithm characteristics, can better improve the image processing efficiency and visual effects, and achieve precise application of image colorization.
Keywords:colorization  partial differential equation  image fusion  image segmentation  infrared image  sparse representation
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