Color Balance and Fusion for Underwater Image Enhancement

A successful method is initiated to the underwater images which get skint due to the absorption and medium scattering. Image structure’s underwater information or any hardware is not required. The two images that are derived straight from a color – compensated and white – balanced description of the original tarnished images are figured on this. The output image’s color contrast and edges are defined by these two images which tend to fusion and also their related weight maps. A multiscale fusion strategy is personalized to avoid the pointed weight map transitions that create artifacts when low frequency components are used for the reconstructed image. Our widespread qualitative and quantitative assessment proves that our superior images and videos are considered by better protection of the dark regions, better global difference and edge sharpness. The exactness of numerous image processing applications, such as image segmentation and keypoint matching are enhanced by our algorithm since it is independent on the camera settings.

[1]  Aamir Saeed Malik,et al.  Underwater image enhancement by wavelet based fusion , 2016, 2016 IEEE International Conference on Underwater System Technology: Theory and Applications (USYS).

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

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

[4]  Pamela C. Cosman,et al.  Underwater Image Restoration Based on Image Blurriness and Light Absorption , 2017, IEEE Transactions on Image Processing.

[5]  Pei-Yin Chen,et al.  Low Complexity Underwater Image Enhancement Based on Dark Channel Prior , 2011, 2011 Second International Conference on Innovations in Bio-inspired Computing and Applications.

[6]  Codruta O. Ancuti,et al.  Color Balance and Fusion for Underwater Image Enhancement , 2018, IEEE Transactions on Image Processing.

[7]  Omer Deperlioglu,et al.  Underwater image enhancement based on contrast adjustment via differential evolution algorithm , 2016, 2016 International Symposium on INnovations in Intelligent SysTems and Applications (INISTA).