View License

Download apps, toolboxes, and other File Exchange content using Add-On Explorer in MATLAB.

» Watch video

Highlights from
Fast Noise Estimation in Images

Join the 15-year community celebration.

Play games and win prizes!

» Learn more

4.0
4.0 | 1 rating Rate this file 27 Downloads (last 30 days) File Size: 1.6 KB File ID: #36941 Version: 1.0

Fast Noise Estimation in Images

by

Tolga Birdal (view profile)

 

Estimate the standard deviation of the noise in a gray-scale image.

| Watch this File

File Information
Description

This is an extremely simple m-file which implements the method described in :
J. Immerkær, “Fast Noise Variance Estimation”, Computer Vision and Image Understanding, Vol. 64, No. 2, pp. 300-302, Sep. 1996
 
The function inputs a grayscale image I and returns Sigma, the noise estimate. Here is a sample use:

I = rgb2gray(imread('sample.jpg'));
Sigma=estimate_noise(I);
         
The advantage of this method is that it includes a Laplacian operation which is almost insensitive to image structure but only depends on the noise in the image.

Acknowledgements

Noise Level Estimation From A Single Image inspired this file.

Required Products Image Processing Toolbox
MATLAB release MATLAB 7.9 (R2009b)
Tags for This File   Please login to tag files.
Please login to add a comment or rating.
Comments and Ratings (3)
20 May 2016 Rukundo

In this source code, is M=[1 -2 1; -2 4 -2; 1 -2 1] correct ? I am asking this because the Laplacian kernel is M=[0 -1 0; -1 4 -1; 0 -1 0]. Please tell me which one is correct.

Comment only
21 Apr 2015 Sanchari Sengupta

This might sound very lame but can you please tell guide me from point to point as to how to run this file? Its very urgent

Comment only
27 Nov 2012 Youssef Khmou

Youssef Khmou (view profile)

 

Contact us