Performance analysis of Non Linear Filtering Algorithms for underwater images

Image filtering algorithms are applied on images to remove the different types of noise that are either present in the image during capturing or injected in to the image during transmission. Underwater images when captured usually have Gaussian noise, speckle noise and salt and pepper noise. In this work, five different image filtering algorithms are compared for the three different noise types. The performances of the filters are compared using the Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE). The modified spatial median filter gives desirable results in terms of the above two parameters for the three different noise. Forty underwater images are taken for study.

An Optimal Method For Wake Detection In SAR Images Using Radon Transformation Combined With Wavelet Filters

A new fangled method for ship wake detection in synthetic aperture radar (SAR) images is explored here. Most of the detection procedure applies the Radon transform as its properties outfit more than any other transformation for the detection purpose. But still it holds problems when the transform is applied to an image with a high level of noise. Here this paper articulates the combination between the radon transformation and the shrinkage methods which increase the mode of wake detection process. The latter shrinkage method with RT maximize the signal to noise ratio hence it leads to most optimal detection of lines in the SAR images. The originality mainly works on the denoising segment of the proposed algorithm. Experimental work outs are carried over both in simulated and real SAR images. The detection process is more adequate with the proposed method and improves better than the conventional methods.