Computer Engineering and Applications ›› 2022, Vol. 58 ›› Issue (11): 23-32.DOI: 10.3778/j.issn.1002-8331.2112-0280

• Research Hotspots and Reviews • Previous Articles     Next Articles

Research Review of Space-Frequency Domain Image Enhancement Methods

GUO Yongkun, ZHU Yanchen, LIU Liping, HUANG Qiang   

  1. 1.College of Computer Science, Jiangxi University of Traditional Chinese Medicine, Nanchang 330004, China
    2.Network Center, Jiangxi University of Traditional Chinese Medicine, Nanchang 330004, China
  • Online:2022-06-01 Published:2022-06-01



  1. 1.江西中医药大学 计算机学院,南昌 330004
    2.江西中医药大学 网络中心,南昌 330004

Abstract: For small sample image data sets, the image enhancement method is often used to expand the amount of data to increase the rationality of the experiment. The image enhancement algorithm can improve the overall and local contrast of the image, highlight the detailed information of the image, make the image more in line with the visual characteristics of human eyes and easy to be recognized by the machine. In order to deeply study the new ideas and new directions in the application field of image enhancement, starting from the basic principle of image enhancement algorithms, based on the basic principle of image enhancement algorithms, this paper summarizes two kinds of image enhancement algorithms widely used in spatial domain and frequency domain in recent years, including histogram equalization image enhancement algorithm, gray transformation image enhancement algorithm, spatial filter image enhancement algorithm and frequency domain filter image enhancement algorithm. And their basic concepts and related definitions are introduced in detail, and their advantages and disadvantages are briefly described. In addition, subjective and objective evaluation methods are used to compare and analyze the enhancement effects of these algorithms, and the advantages and disadvantages, applicable scenarios and complexity of each algorithm are compared and analyzed, so as to further study the hidden useful information of each image enhancement algorithm, and find out the image enhancement methods with stronger robustness and applicability. Experimental results show that different algorithms have their own characteristics, for different image effects, spatial image enhancement method is more suitable for enhancing contrast, and frequency domain image enhancement method is more suitable for highlighting details. A single method can not meet the needs of image processing, and the image enhancement algorithm combined with advantages is more meaningful. The in-depth study of these algorithms can bring new opportunities for researchers, expand new research directions, promote the high-level development of the whole image enhancement technology, and make image enhancement technology play an important role in many subject fields.

Key words: image enhancement, frequency domain algorithm, spatial domain algorithm

摘要: 对于小样本图像数据集往往采用图像增强的方法扩充数据量增加实验的合理性,图像增强算法能够提高图像整体和局部的对比度,突出图像的细节信息,使图像更符合人眼的视觉特性且易于机器识别。为了深入研究图像增强应用的新思路、新方向,从图像增强算法的基本原理出发,归纳总结了近年来应用比较广泛的空域和频域两大类图像增强算法,包括直方图均衡图像增强算法、灰度变换图像增强算法、空域滤波图像增强算法和频域滤波图像增强算法,分别详细介绍了它们的基本概念和相关定义并简述了其浅层面的优缺点。另外采用主观和客观的评价方法对这些算法的增强效果进行了对比和分析,并对各算法的优缺点、适用场景和复杂度进行了对比分析,以更深入研究各个图像增强算法的隐含有用信息,以找出鲁棒性、适用性更强的图像增强方法。实验结果表明,不同的算法都具有各自的特点,针对不同的图像效果不同,增强对比度更适宜采用空域图像增强方法,突出细节更适宜采用频域图像增强方法。单一的方法无法满足图像处理的需要,优势结合的图像增强算法更有研究意义。对这些算法的深入研究能够为研究者带来新的契机,拓展新的研究方向,推动整个图像增强技术高水平发展,使图像增强技术在多个学科领域发挥重要作用。

关键词: 图像增强, 频域算法, 空域算法