Image Processing Toolbox User's Guide |
Deblurring Model
A blurred or degraded image can be approximately described by this equation g = Hf + n, where
Note The image f really doesn't exist. This image represents what you would have if you had perfect image acquisition conditions. |
Importance of the PSF
Based on this model, the fundamental task of deblurring is to deconvolve the blurred image with the PSF that exactly describes the distortion. Deconvolution is the process of reversing the effect of convolution.
To illustrate, this example takes a clear image and deliberately blurs it by convolving it with a PSF. The example uses the fspecial
function to create a PSF that simulates a motion blur, specifying the length of the blur in pixels, (LEN=31
), and the angle of the blur in degrees (THETA=11
). Once the PSF is created, the example uses the imfilter
function to convolve the PSF with the original image, I
, to create the blurred image, Blurred
. (To see how deblurring is the reverse of this process, using the same images, see Deblurring with the Wiener Filter.)
I = imread('peppers.png'); I = I(60+[1:256],222+[1:256],:); % crop the image figure; imshow(I); title('Original Image'); LEN = 31; THETA = 11; PSF = fspecial('motion',LEN,THETA); % create PSF Blurred = imfilter(I,PSF,'circular','conv'); figure; imshow(Blurred); title('Blurred Image');
Understanding Deblurring | Using the Deblurring Functions |
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