  This report describes the experimental analysis of proposed underwater image
enhancement algorithms based on partial differential equations (PDEs). The
algorithms perform simultaneous smoothing and enhancement due to the
combination of both processes within the PDE-formulation. The framework enables
the incorporation of suitable colour and contrast enhancement algorithms within
one unified functional. Additional modification of the formulation includes the
combination of the popular Contrast Limited Adaptive Histogram Equalization
(CLAHE) with the proposed approach. This modification enables the hybrid
algorithm to provide both local enhancement (due to the CLAHE) and global
enhancement (due to the proposed contrast term). Additionally, the CLAHE clip
limit parameter is computed dynamically in each iteration and used to gauge the
amount of local enhancement performed by the CLAHE within the formulation. This
enables the algorithm to reduce or prevent the enhancement of noisy artifacts,
which if present, are also smoothed out by the anisotropic diffusion term
within the PDE formulation. In other words, the modified algorithm combines the
strength of the CLAHE, AD and the contrast term while minimizing their
weaknesses. Ultimately, the system is optimized using image data metrics for
automated enhancement and compromise between visual and quantitative results.
Experiments indicate that the proposed algorithms perform a series of functions
such as illumination correction, colour enhancement correction and restoration,
contrast enhancement and noise suppression. Moreover, the proposed approaches
surpass most other conventional algorithms found in the literature.
