Color fidelity and visibility enhancement of underwater image de-hazing by enhanced fuzzy intensification operator

This paper presents an optimization based algorithm for underwater image de-hazing problem. Underwater image de-hazing is the most prominent area in research. Underwater images are corrupted due to absorption and scattering. With the effect of that, underwater images have the limitation of low visibility, low color and poor natural appearance. To avoid the mentioned problems, Enhanced fuzzy intensification method is proposed. For each color channel, enhanced fuzzy membership function is derived. Second, the correction of fuzzy based pixel intensification is carried out for each channel to remove haze and to enhance visibility and color. The post processing of fuzzy histogram equalization is implemented for red channel alone when the captured image is having highest value of red channel pixel values. The proposed method provides better results in terms maximum entropy and PSNR with minimum MSE with very minimum computational time compared to existing methodologies.

[1]  Madasu Hanmandlu,et al.  An Optimal Fuzzy System for Color Image Enhancement , 2006, IEEE Transactions on Image Processing.

[2]  Huimin Lu,et al.  Underwater image dehazing using joint trilateral filter , 2014, Comput. Electr. Eng..

[3]  Wen Gao,et al.  Single underwater image enhancement with a new optical model , 2013, 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013).

[4]  Vishalkirthi S. Patil,et al.  Haze removal and fuzzy based enhancement of image , 2016, 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC).

[5]  Andrea Cavallaro,et al.  Hierarchical rank-based veiling light estimation for underwater dehazing , 2015, BMVC.

[6]  Codruta O. Ancuti,et al.  Enhancing underwater images and videos by fusion , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[7]  Adrian Galdran,et al.  Automatic Red-Channel underwater image restoration , 2015, J. Vis. Commun. Image Represent..

[8]  Raimondo Schettini,et al.  Underwater Image Processing: State of the Art of Restoration and Image Enhancement Methods , 2010, EURASIP J. Adv. Signal Process..

[9]  Bobby Bodenheimer,et al.  Synthesis and evaluation of linear motion transitions , 2008, TOGS.

[10]  Jian Wang,et al.  Single underwater image restoration by blue-green channels dehazing and red channel correction , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[11]  N Carlevaris-Bianco,et al.  Initial results in underwater single image dehazing , 2010, OCEANS 2010 MTS/IEEE SEATTLE.

[12]  Huimin Lu,et al.  Contrast enhancement for images in turbid water. , 2015, Journal of the Optical Society of America. A, Optics, image science, and vision.

[13]  M. S. Hitam,et al.  Mixture contrast limited adaptive histogram equalization for underwater image enhancement , 2013, 2013 International Conference on Computer Applications Technology (ICCAT).

[14]  Zohair Al-Ameen Visibility Enhancement for Images Captured in Dusty Weather via Tuned Tri-threshold Fuzzy Intensification Operators , 2016 .

[15]  Jian Wang,et al.  Single underwater image enhancement based on color cast removal and visibility restoration , 2016, J. Electronic Imaging.

[16]  Ying-Ching Chen,et al.  Underwater Image Enhancement by Wavelength Compensation and Dehazing , 2012, IEEE Transactions on Image Processing.

[17]  Maitreyee Dutta,et al.  An Approach for Shallow Underwater Images Visibility and Color Improvement , 2015 .

[18]  V. Magudeeswaran,et al.  Fuzzy Logic-Based Histogram Equalization for Image Contrast Enhancement , 2013 .

[19]  Raanan Fattal,et al.  Single image dehazing , 2008, ACM Trans. Graph..

[20]  Silvia Silva da Costa Botelho,et al.  Achieving Turbidity Robustness on Underwater Images Local Feature Detection , 2015, BMVC.

[21]  Shuhuan Wen,et al.  Restoration and Enhancement of Underwater Images Based on Bright Channel Prior , 2016 .

[22]  C. J. Prabhakar,et al.  An Image Based Technique for Enhancement of Underwater Images , 2012, ArXiv.

[23]  Runmin Cong,et al.  Underwater Image Enhancement by Dehazing With Minimum Information Loss and Histogram Distribution Prior , 2016, IEEE Transactions on Image Processing.

[24]  Huimin Lu,et al.  Single image dehazing through improved atmospheric light estimation , 2015, Multimedia Tools and Applications.