Uniform Distorted Scene Reduction on Distribution of Colour Cast Correction
Scene in the photo occulated by uniform particles distribution can degrade the image quality accidently. State of the art pre-processing methods are able to enhance visibility by employing local and global filters on the image scene. Regardless of air light and transmission map right estimation, those methods unfortunately produce artifacts and halo effects because of uncorrelated problem between the global and local filter’s windows. Besides, previous approaches might abruptly eliminate the primary scene structure of an image like texture and colour. Therefore, this study aims not solely to improve scene image quality via a recovery method but also to overcome image content issues such as the artefacts and halo effects, and finally to reduce the light disturbance in the scene image. We introduce our proposed visibility enhancement method by using joint ambience distribution that improves the colour cast in the image. Furthermore, the method is able to balance the atmospheric light in correspondence to the depth map accordingly. Consequently, our method maintains the image texture structural information by calculating the lighting estimation and maintaining a range of colours simultaneously. The method is tested on images from the Benchmarking Single Image Dehazing research by assessing their clear edge ratio, gradient, range of saturated pixels, and structural similarity metric index. The scene image restoration assessment results show that our proposed method had outperformed resuls from the Tan, Tarel and He methods by gaining the highest score in the structural similarity index and colourfulness measurement. Furthermore, our proposed method also had achieved acceptable gradient ratio and percentage of the number of saturated pixels. The proposed approach enhances the visibility in the images without affecting them structurally.
Ahmed, H.S. and M.J. Nordin, Improving diagnostic viewing of medical images using enhancement algorithms. Journal of Computer Science, 2011. 7(12): p. 1831.
Huddin, A.B., et al., Enhancement techniques for MRI human spine images. Jumal Teknologi, 2015. 77.
Talib, M.L.B., M.F. Nasrudin, and S.N.H.S. Abdullah. A study of uniform scene distorted removal based on contrast recovery. in Advances in Electrical, Electronic and Systems Engineering (ICAEES), International Conference on. 2016. IEEE.
Bansal, B., J. Singh Sidhu, and K. Jyoti, A Review of Image Restoration based Image Defogging Algorithms. International Journal of Image, Graphics and Signal Processing, 2017. 9(11): p. 62-74.
He, K., J. Sun, and X. Tang, Single image haze removal using dark channel prior. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2011. 33(12): p. 2341-2353.
Shi, L., et al. Image haze removal using dark channel prior and minimizing energy function. in Technology, Networking, Electronic and Automation Control Conference (ITNEC), 2017 IEEE 2nd Information. 2017. IEEE.
Qing, C., et al. Image Haze Removal Using Depth-Based Cluster and Self-Adaptive Parameters. in Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 2017 IEEE International Conference on. 2017. IEEE.
Tan, R.T. Visibility in bad weather from a single image. in Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on. 2008. IEEE.
Talib, M.L., S.N.H.S. Abdullah, and M.F. Nasruddin. Uniform scene distorted removal in single image based on illumination information. in Electrical Engineering and Informatics (ICEEI), 2017 6th International Conference on. 2017. IEEE.
Hautière, N., J.-P. Tarel, and D. Aubert. Towards fog-free in-vehicle vision systems through contrast restoration. in Computer Vision and Pattern Recognition, 2007. CVPR'07. IEEE Conference on. 2007. IEEE.
Tarel, J.-P. and N. Hautiere. Fast visibility restoration from a single color or gray level image. in Computer Vision, 2009 IEEE 12th International Conference on. 2009. IEEE.
Tarel, J.-P., et al., Vision enhancement in homogeneous and heterogeneous fog. Intelligent Transportation Systems Magazine, IEEE, 2012. 4(2): p. 6-20.
Yahya, S.R., et al. Review on image enhancement methods of old manuscript with the damaged background. in Electrical Engineering and Informatics, 2009. ICEEI'09. International Conference on. 2009. IEEE.
14. Tarel, J.-P., et al. Improved visibility of road scene images under heterogeneous fog. in Intelligent Vehicles Symposium (IV), 2010 IEEE. 2010. IEEE.
Parthasarathy, S. and P. Sankaran. A RETINEX based haze removal method. in Industrial and Information Systems (ICIIS), 2012 7th IEEE International Conference on. 2012. IEEE.
Xie, B., F. Guo, and Z. Cai. Improved single image dehazing using dark channel prior and multi-scale Retinex. in Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on. 2010. IEEE.
Zhou, J. and F. Zhou. Single image dehazing motivated by Retinex theory. in Instrumentation and Measurement, Sensor Network and Automation (IMSNA), 2013 2nd International Symposium on. 2013. IEEE.
Fattal, R., Dehazing using color-lines. ACM Transactions on Graphics (TOG), 2014. 34(1): p. 13.
Fattal, R. Single image dehazing. in ACM transactions on graphics (TOG). 2008. ACM.
Pal, N.S., S. Lal, and K. Shinghal, Modified Visibility Restoration-Based Contrast Enhancement Algorithm for Colour Foggy Images. IETE Technical Review, 2017: p. 1-14.
He, L., et al., Haze Removal Using the Difference- Structure-Preservation Prior. IEEE Trans Image Process, 2017. 26(3): p. 1063-1075.
Xiong, Y., H. Yan, and C. Yu, Improved haze removal algorithm using dark channel prior. Journal of Computational Information Systems, 2013. 9(14): p. 5743-5750.
Yeh, C.-H., et al. Efficient image/video dehazing through haze density analysis based on pixel-based dark channel prior. in Information Security and Intelligence Control (ISIC), 2012 International Conference on. 2012. IEEE.
Zhu, Q., J. Mai, and L. Shao, A fast single image haze removal algorithm using color attenuation prior. Image Processing, IEEE Transactions on, 2015. 24(11): p. 3522-3533.
Al-Sammaraie, M.F. Contrast enhancement of roads images with foggy scenes based on histogram equalization. in Computer Science & Education (ICCSE), 2015 10th International Conference on. 2015. IEEE.
Jha, D.K., B. Gupta, and S.S. Lamba, l 2-norm-based prior for haze-removal from single image. IET Computer Vision, 2016. 10(5): p. 331-343.
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