Averaging corrupted images to eliminate the noise

Posted by Mertie Pertie on Stack Overflow See other posts from Stack Overflow or by Mertie Pertie
Published on 2010-03-15T19:16:11Z Indexed on 2010/03/15 19:19 UTC
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Hi all

As you can get it from the title, I want to average some .jpg images which are corrupted by zero-mean Gaussian additive. After searching over internet, I figured out to add image matrices and divide the sum by the # of matrices. However the resultant image is totally black. Normally when the number of image increases then the resultant image gets better. But When I use more images it gets darker.

I am using 800x600 black and white images with .jpg ext

Here is the script I used;

image1 = imread ('PIC1.jpg'); image2 = imread ('PIC2.jpg'); image3 = imread ('PIC3.jpg'); image4 = imread ('PIC4.jpg');

sum = image1 + image2 + image3 + image4; av = sum / 4; imshow(av);

Thanks in advance

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