Assignment I

Assignment I - known Low-pass filter, it is possible to...

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Medical Imaging III Assignment 1 Dhairya Pujara (12096058) Page | 1 4/12/2011 Original to be deconvoluted: Bars-G10-P30 Inverse filter with thresholding 0.15 (say) Regularized inverse filtering parameter 0.15 Richardson-Lucy 10 iterations Richardson-Lucy 30 iterations Uncorrupted image
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Medical Imaging III Assignment 1 Dhairya Pujara (12096058) Page | 2 4/12/2011 Original to be deconvoluted: PSF-Bars Inverse filtering with thresholding 0.025 Inverse filtering with thresholding 0.015 Regularized inverse filtering 0.009 Richardson-Lucy 10 iterations Richardson-Lucy 30 iterations
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Medical Imaging III Assignment 1 Dhairya Pujara (12096058) Page | 3 4/12/2011 Conclusion: After studying the resulting image from different deconvolution, we can infer that the inverse filtering technique (a restoration technique for deconvolution, i.e., when the image is blurred by a
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Unformatted text preview: known Low-pass filter, it is possible to recover the image) is very sensitive to additive noise. Since the inverse filter is a form of High-pass filer, inverse filtering responds very badly to any noise that is present in the image because noise tends to be of high frequency. For Richardson-Lucy, we conclude that as the number of iteration we performed on the image increased, the better quality output image was realized. This filter is particularly interesting as it could remove much of the blur and still leave the noise in the image. This was not the case with previous filter. So overall, based upon their input parameters and way of processing images (deconvoluting in this case), we can conclude that Richardson-Lucy performs better without noise information, however the other two methods require noise information to give better results....
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Assignment I - known Low-pass filter, it is possible to...

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