DIP Homework 3
Due: December 23, 2018
1 Satellite images can be degraded by atmospheric turbulence, which we try to model
as linear, shift-invariant blurring with an isotropic Gaussian impulse response (with
unknown standard deviation) plus additive white noise (with unknown variance).
Please download hw3_satellite_1_degraded.tiff and hw3_satellite_2_degraded.tiff
from the webpage.
(a) Design and implement a method to estimate the standard deviation of the
additive white noise directly from the degraded image. For each image, report the
estimated noise standard deviation, assuming image intensity values in the range
[0,1].
(b) Design and implement a method to estimate the standard deviation of the
Gaussian impulse response directly from the degraded image. For each image,
report the estimated Gaussian standard deviation.
(c) Perform. inverse filtering on each image, using the estimated Gaussian impulse
response from Part B (function: deconvwnr with a noise estimate of 0). Submit the
inverse filtered image. Comment on the quality of the restored image.
(d) Perform. Wiener filtering on each image, using the estimated noise standard
deviation from Part A and the estimated Gaussian impulse response from Part B
(function: deconvwnr). Submit the Wiener filtered image. Comment on the quality
of the restored image and compare to the result from Part C.
2 Please download the image hw3_insurance_form.jpg from the webpage. During
faxing, the form. has suffered some image distortions: it is slightly rotated and some
portions of the table’s horizontal and vertical lines have been erased. Design and
implement an image processing algorithm to automatically rotate the form. to an
upright orientation and repair the gaps in the broken lines. Clearly describe the steps
in your algorithm, showing intermediate results for clarification if helpful. Display
and submit the final restored image.
Instructions for turning in the homework:
Submit your PDF report and the relevant MATLAB codes named
studentnumber_HW3.pdf via course web.