Research Review of Space-Frequency Domain Image Enhancement Methods
Computer Engineering and Applications
2022, 58 ( 11):
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.
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