Abstract
Abstract
Images acquired in underwater environments are usually affected by light absorption and scattering. These are the two phenomena that reduce the clarity of images that are captured in these environments. These factors cause low contrast and anamorphic colour diffusion. To tackle these issues, we propose an optimized low contrast enhancement scheme. The main thrust of this paper borders on enhancement of underwater image contrast by preserving the brightness level. The approach is termed Fuzzy-Histogram Equalisation Optimised for Brightness Preservation (FHEOBP) technique, where a combination of fuzzy and classical histogram equalisation techniques is employed towards the enhancement of the contrast of images from underwater scene. The scheme is optimized using teaching-learning-based optimisation technique that is built into the algorithm. The proposed FHEOBP filter shows improved performance over Local Histogram Equalisation (LHE) and Global Histogram Equalisation (GHE) as it has a higher luminance distortion index value than those of LHE and GHE. This translates into a better image details preservation. In fact, the computed luminance distortion indices for optimised FHEOBP are 16.4%, 28.3% and 20.1%, respectively higher than those of the corresponding GHE, in the same test images utilised for performance evaluation. Between the optimised and non-optimised FHEOBP, luminance distortion figures of optimised FHEOBP are 8%, 6.8% and 9.8% higher than those of the equivalent non-optimised FHEOBP in the test image data set.