Underwater acoustic image enhancement using wavelet and K-L transform

Image enhancement techniques play a vital role in improving the quality of the low resolution images. There are recent methods that are employed for enhancing the digital images which do not suit for low resolution underwater acoustic images. Many common approaches used in vision and pattern recognition turned to be inefficient because of the nature of the noise present in acoustic images. For enhancing the acoustic images, a method which uses discrete wavelet transform to decompose the image into Low-Low, Low-High, High-Low and High-High components is proposed. Then the Low-Low frequency component is enhanced using Karhumen-Loeve (K-L) transform to estimate a new enhanced LL component. The difference image is obtained by subtracting the enhanced LL component with the original LL component. Other three high frequency components are also interpolated and added with the difference image. These enhanced components are reconstructed using Inverse discrete wavelet transform. The resultant enhanced image has better contrast and resolution compared to the images obtained by Generalized histogram equalization (GHE) and by using Singular Value Decomposition (SVD) approach. The experimental results show that the proposed system outperforms the GHE and SVD methods in terms of image enhancement.