Analytical Comparison of Noise Reduction Filters for Image Restoration Using SNR Estimation

12/02/2014
by   Poorna Banerjee Dasgupta, et al.
0

Noise removal from images is a part of image restoration in which we try to reconstruct or recover an image that has been degraded by using apriori knowledge of the degradation phenomenon. Noises present in images can be of various types with their characteristic Probability Distribution Functions (PDF). Noise removal techniques depend on the kind of noise present in the image rather than on the image itself. This paper explores the effects of applying noise reduction filters having similar properties on noisy images with emphasis on Signal-to-Noise-Ratio (SNR) value estimation for comparing the results.

READ FULL TEXT

page 2

page 3

page 4

research
06/16/2015

Evaluation of Denoising Techniques for EOG signals based on SNR Estimation

This paper evaluates four algorithms for denoising raw Electrooculograph...
research
01/19/2019

Image De-Noising For Salt and Pepper Noise by Introducing New Enhanced Filter

When an image is formed, factors such as lighting (spectra, source, and ...
research
02/19/2015

Application of Independent Component Analysis Techniques in Speckle Noise Reduction of Retinal OCT Images

Optical Coherence Tomography (OCT) is an emerging technique in the field...
research
02/04/2016

Fundamental Limits in Multi-image Alignment

The performance of multi-image alignment, bringing different images into...
research
02/22/2016

Denoising and Covariance Estimation of Single Particle Cryo-EM Images

The problem of image restoration in cryo-EM entails correcting for the e...
research
02/08/2020

Ramifications and Diminution of Image Noise in Iris Recognition System

Human Identity verification has always been an eye-catching goal in digi...
research
09/20/2016

Markov Random Field Model-Based Salt and Pepper Noise Removal

Problem of impulse noise reduction is a very well studied problem in ima...

Please sign up or login with your details

Forgot password? Click here to reset