A QUANTITIVE EVALUATION OF VARIOUS SPATIAL FILTERS FOR UNDERWATER SONAR IMAGES DENOISING APPLICATION

Image denoising is a key issue in all image processing researches. The great challenge of image denoising is how to preserve the edges and all fine details of an image when reducing the noise. In this paper, a comparative study of image denoising techniques for underwater SONAR (Sound Navigation and Ranging) images relying on spatial filters is presented. In particular four types of spatial filters (Average, Gaussian, Laplacian of Gaussian and Median filters) are applied to judge the efficiency. On each image, different window size configurations starting from 3×3 to 29×29 are applied and the performances of image filtering techniques are analyzed by the estimation of parametric values such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and execution time for filtering the images. It is observed that by increasing the window size the execution time will increase and PSNR values will decrease. With this analysis and from the results it is found that the optimum filter is Gaussian and the optimum window size is 3×3 for the underwater SONAR images which gives the best execution time, MSE and the PSNR value (37.87dB). [PUBLICATION ABSTRACT]