Abstract
The aerial image is the process of taking images from the air and it is greatly important in various applications such the knowing the surface of the earth, studying agricultural lands and large pastures such as forests, identifying natural disasters and studying them to avoid them in the future and other areas. However, these images are often hazy. Consequently, the objective of this research was to enhance aerial images by focusing on optimizing the lighting aspect through the application of retinex theory. Subsequently, the enhancement of colors and preservation of vital information were pursued utilizing the Dark Channel Prior (DCP) technique alongside the HSV color space. Finally, a guided filter was employed to effectively eliminate noise from the aerial images. Therefore, analysing the results and comparing the proposed method with several other methods has the best measures of quality for our data reached its values CM(39.577), LOE(159.304) and NIQE(2.721), and it succeeded in improving lighting and retrieving colour information.
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References
H. Saadiyah, S. Mahdi, Effect of climate change on spring massive sand/dust storms in Iraq. Al-Mustansiriyah J. Sci. 32, 4 (2021)
R. Abbas, A. Abbas, H. Daway, Medical images enhanced by using fuzzy logic depending on contrast Stretch membership function. Int. J. Intell. Eng. Syst. 14(1), 368–375 (2021)
G. Karam, Z. Abood, H. Kareem, H. Dowy, Blurred image restoration with unknown point spread function. Al-Mustansiriyah J. Sci., 29, (2018)
D.Mohammed, and J.Kadhum. Evaluation of Atmospheric Blocking effects on Weather events in Iraq. Al-Mustansiriyah J. Sci. 31, no. 4 (2020)
R. Gonzalez, P. 2 Wintz, nd, Digital Image Processing 2nd Edition Addison Wesley, Reading, Mass, (1987)
C. Ancuti, C. Ancuti, Single image dehazing by multi-scale fusion. IEEE Trans. Image Process. 22(8), 3271–3282 (2013)
K. He, J. Sun, X. Tang, Single image haze removal using dark channel prior. IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2341–2353 (2010)
D. Berman, S. Avidan, Non-local image dehazing, in Proceedings of the IEEE conference on computer vision and pattern recognition, 1674–1682,(2016)
D. Park, H. Park, D. Han, H. Ko, Single image dehazing with image entropy and information fidelity, in 2014 IEEE International Conference on Image Processing (ICIP), IEEE, 4037–4041,(2014)
F. Dharejo, Y. Zhou, F. Deeba, Y. Du, A color enhancement scene estimation approach for single image haze removal. IEEE Geosci. Remote Sens. Lett. 17(9), 1613–1617 (2019)
D. Jobson, Z. Rahman, G. Woodell, Statistics of visual representation, in visual information processing XI. Int. Soc. Opt. Photonics, 25–35(2002)
H. Kareem, R. Saihood, Aerial image enhancement based on YCbCr Color Space. Int. J. Intell. Eng. Syst. 14(6), 177–186 (2021)
D. Ngo, S. Lee, G.-D. Lee, B. Kang, Single-image visibility restoration: a machine learning approach and its 4K-capable hardware accelerator. Sensors. 20(20), 5795 (2020)
E. Land, J. McCann, Lightness and retinex theory. Josa. 61(1), 1–11 (1971)
C. Shen, W. Hwang, Color image enhancement using retinex with robust envelope, in 2009 16th IEEE International Conference on Image Processing (ICIP), IEEE, 3141–3144(2009)
H. Li, B. Manjunath, S. Mitra, Multisensor image fusion using the wavelet transform. Graph Model. Image Process. 57(3), 235–245 (1995)
M. Iqbal, M. Riaz, A. Ghafoor, S. Ali, A. Ahmad, Guided image filtering using data mining and decomposition. Imaging Sci. J. 67(5), 261–267 (2019)
U.S. California, U.S.C.-S.I.P.I. Image Database, USC-SIPI Image Database, (2020)
H. David, E. Suesstrunk, Measuring colorfulness in natural images,Human Vision and Electronic Imaging VIII, SPIE, 87–95,(2003)
S. Wang, J. Zheng, M. Hu, B. Li, Naturalness preserved enhancement algorithm for non-uniform illumination images. IEEE Trans. Image Process. 22(9), 3538–3548 (2013)
A. Mittal, R. Soundararajan, A. Bovik, Making a ‘completely blind’ image quality analyzer. IEEE Signal. Process. Lett. 20(3), 209–212 (2012)
A. Hashim, H. Daway, H. kareem, No reference image quality measure for hazy images. Int. J. Intell. Eng. Syst. 13(6), 460–471 (2020)
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Khalaf, N.A., Daway, H.G. & Ahmed, B.M. Aerial images enhancement using retinex with colour preservation and noise reduction. J Opt (2024). https://doi.org/10.1007/s12596-024-01847-5
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DOI: https://doi.org/10.1007/s12596-024-01847-5