Survey on Dehazing of Multispectral Images

Authors

DOI:

https://doi.org/10.26713/cma.v14i2.2443

Keywords:

Dehazing, Multispectral images, Contrastive learning, CycleGAN, Deep learning

Abstract

Images captured in hazy climate can be severely decayed by atmospheric particle scattering, which reduces disparity, and which makes it hard to identify features of an object with the naked human eye. Image defogging is done to get rid of the weather factor effects which in turn improves the image quality of the image. This article gives a brief summary regarding the image denoising techniques that have been proposed. We performed the various approaches in order to find out which is the best method for achieving the perfect result. All methods are analyzed and the corresponding subcategories are presented in accordance with the principles and characteristics. Then, the different methods of quality assessment are described, classified and confidentially discussed. To realize this, we use multispectral sensing. When using filters to divide the wavelengths, multispectral imaging can collect image data in specific wavelength ranges across the spectrum. It can allow for the extraction of additional data that the human eye’s visible red, green, and blue color receptors cannot record. Its ideal use was for the identification and reconnaissance of military targets. This system was also used by ISRO to receive high resolution images from their satellite. The proposed method was applied to various types of multispectral images, where its effectiveness for visualizing spectral features was verified.

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Published

18-09-2023
CITATION

How to Cite

Kayalvizhi, S., Karthikeyan, B., Sathvik, C., & Gautham, C. (2023). Survey on Dehazing of Multispectral Images. Communications in Mathematics and Applications, 14(2), 1113–1125. https://doi.org/10.26713/cma.v14i2.2443

Issue

Vol. 14 No. 2 (2023)

Section

Review Article

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