Medical Image Denoising using Spatial Filtering Techniques |
Author(s): |
Ishant Premi , Thapar Polytechnic, Patiala |
Keywords: |
Image denoising, spatial filtering, guided filter, bilateral filter, Gaussian noise |
Abstract |
Image denoising is one of the most important and well known challenges in Computer Vision, Image and video processing fields. The objective of denoising process is to obtain noise free image from the noise-contaminated version of original image. Noise can be intrinsic or extrinsic. There are many reasons for presence of noise in the image. For example like Extrinsic noise contains environment variable and intrinsic noise contains hardware part like sensor of cameras. Nose can’t be avoided so it can be filtered out from the processed image. There are various application areas lik Image Restoration, Image Registration, Image Segmentation, Image Classification and others where the role of image denoising is important. Different types of images inherit different types of noise and so for these different types of noises there are different noise models are used. Denoising method tends to be problem specific and depends upon the type of image and noise model. In medical imaging the filtering of images is first and fundamental step so that final image is better and can be further processed for other purposes. The aim of this paper is to implement and compare various medical image denoising techniques such as Bilateral Filter (BF), Fast Bilateral Filter (FBF) and Guided Filter for denoising the images. Performance Parameters used for evaluation of gray scale images are Peak Signal to Noise Ratio (PSNR), Normalized Absolute Error (NAE), Entropy, Mean Square Error (MSE), Correlation and Visual Quality. |
Other Details |
Paper ID: IJSRDV4I20639 Published in: Volume : 4, Issue : 2 Publication Date: 01/05/2016 Page(s): 1853-1856 |
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