An Effective Approach of Noise Analysis on Images

Here it is represented an image analysis technique using both noising & de-noising process. By taking a simple image of different formats we added a noise i. e. Gaussian noise to the particular image and then the calculation of SNR(SIGNAL-TO-NOISE RATIO) and PSNR(PEAK SIGNAL-TO-NOISE RATIO) is performed based on the image formats such as jpeg, png, etc. Although there are various types of noise but we considered here the Gaussian noise only. The calculation done is also according to the different functions (blocking, nlfilter, etc. ) and the related categories applied on the simple images. After then the image de-noising is performed on the obtained noised image and the image without any applied function in order to check the comparative analysis of the image containing noise and the de-noised image. The image observed is not as an exact replica of the previous image without noise. Also, there is a vast difference between the SNR and PSNR values of the noised and de-noised image. An image transferred by the sender, if get some distortion like Gaussian noise, then after de-noising process the image observed on the receiver side may be not real and exact, but have less distortion which is a great advantage.