摘要
数字图像复原的目的是将所观测到的退化图像恢复到退化前的原始图像,该恢复过程在很多图像处理应用中至关重要。近年来,图像复原技术虽已得到广泛研究,但仍有值得改进之处。为了使该领域的研究人员对当前各种图像复原方法有较全面的了解,在众多技术文献中选取了具有典型性的95篇来对各种图像复原方法进行分类综述。首先通过对复原技术问题的描述,揭示了复原技术的数学背景;其次以数字图像复原技术发展为主线,将复原方法归结为两大类进行详细讨论。一类是经典图像复原方法,另一类是现代图像复原方法。前者反应复原技术背景与发展过程,后者体现复原技术的发展趋势与面临的困难。最后,在总结全文的基础上,指出在今后进一步研究中值得关注的7项问题。
The goal of digital image restoration is to reconstruct an original scene from a degraded observation. This recovery process is critical to many image processing applications. The digital image restoration approaches has been thoroughly studied in recent years. This problem, however, still has numerous research possibilities. In order to give people a comprehensive knowledge of digital image restoration, some typical approaches are presented and discussed in this paper based on 95 references selected from various literatures in this field. We first describe problems in the digital image restoration and discuss its mathematics background. And then, the review is divided into two parts and discussed thoroughly, according to the development of digital image restoration approaches. One is the classical image restoration approaches, and the other is the modern ones. The former is developed based on the objective that provides an overview on the basic principles and methodologies behind the existing algorithms, and the later is arranged to examine the current trends and the potential of this challenging problem. After the survey is discussed in detail, we make a conclusion for this paper and follow by addressing 7 key issues which remain open in this field.
出处
《中国图象图形学报》
CSCD
北大核心
2009年第9期1764-1775,共12页
Journal of Image and Graphics
基金
国家自然科学基金项目(50675099)
江苏省普通高校研究生科研创新计划项目(CX08B_044Z)
江苏省自然科学基金项目(BK2007197)
关键词
数字图像复
原模糊辨识
神经网络
正则化
小波
支持向量机
digital image restoration, blur identification, neural network, regularization, wavelet, support vector machines