Review on: Image De-noising using Bilateral Filter with Multilinear Discriminant Analysis and SVM
Author(s) -
Rohit Jaspal,
Amandeep Ummat
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/21030-2887
Subject(s) - multilinear map , computer science , linear discriminant analysis , artificial intelligence , pattern recognition (psychology) , support vector machine , image (mathematics) , discriminant , computer vision , mathematics , pure mathematics
Noise removal from magnetic resonance images is important for further processing and visional analysis. Bilateral filter is known for its effective performance in edge-preserved image denoising. Here, an iterative bilateral filter is proposed for filtering the Rician noise in the magnitude magnetic resonance images. It improves the denoising efficiency. It also preserves the fine structures of the image. It also reduces the bias due to Rician noise. Thus we can preserve the quality of image. The quantitative analysis based on the standard metrics like peak signal-to-noise ratio and mean structural similarity index matrix. It shows the proposed method which performs better than the other recently proposed denoising methods for MRI.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom