A study in enhancement of satellite images

被引:0
|
作者
Mini, P. B. [1 ]
Bhomini, P. Amudha [2 ]
机构
[1] Nesamony Mem Christian Coll, Marthandam, India
[2] Nesamony Mem Christian Coll, Dept Comp Applicat, Marthandam, India
关键词
Machine learning; Peak signal-to-noise ratio; Discrete cosine transform; Deep learning; Histogram equalization; ALGORITHM;
D O I
10.1016/j.engappai.2024.109259
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Satellite image enhancement is the method, which is commonly used in the field of satellite image processing for the betterment of the feature visualization and for clear visibility to properly identify those features. These satellite images have many atmospheric barriers like distortion and noise because they are captured from a very high and far distance. After the image capturing, some geometric corrections and radiometric corrections are carried out on those images, but these corrections are not enough for all the applications. So, it is needed to enhance the image restored before using it for feature identification. Nowadays, there are so many approaches for assuring effective image enhancement. However, there are so many drawbacks that need to be addressed in future. Hence, this article illustrates a clear and elaborate survey of various research articles presenting satellite image enhancement methods, such as machine learning-based techniques, optimization-based techniques, wavelet-based techniques, filter-based techniques and Histogram equalization-based techniques. Finally, the analysis is given in the survey based on the classification of research methods, publication year, utilized datasets and performance measures towards enhancement of satellite images. At last, issues and research gaps in methods are given in such a way that the motivation for developing an effective method for enabling effective enhancement is revealed.
引用
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页数:13
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