Visual enhancement of underwater images using Empirical Mode Decomposition and wavelet denoising

In recent years, most underwater vehicles are equipped with optical cameras to capture underwater images. But underwater images acquired using optic cameras have poor visual quality due to propagation of properties of light in water. So it is useful to apply image enhancement methods to increase visual quality of the images as well as enhance interpretability and visibility. In this paper, an Empirical Mode Decomposition (EMD) based underwater image enhancement algorithm is presented for this purpose. In the proposed approach, initially each color channel (R, G, B) of an underwater image is decomposed into Intrinsic Mode Functions (IMFs) using EMD. The first IMF of each component is applied to wavelet denoising. Because this IMF includes all local high spatial frequency components. Then the enhanced image is constructed by combining the IMFs of spectral channels with different weights in order to obtain an enhanced image with increased visual quality. The weight estimation process is carried out automatically using a genetic algorithm that computes the weights of IMFs so as to optimize the sum of the entropy and average gradient of the reconstructed image.