tailieunhanh - Lecture Digital image processing - Lecture 20: Image restoration

This chapter presents the following content: Image formation process and the degradation model, degradation model in continues function and its discrete formulation, discrete formulation for 1D and 2D, estimation of degradation model, by observation, by experimentation, mathematical model, restoration techniques. | Digital Image Processing CSC331 Image restoration 1 Summery of previous lecture Image restoration techniques Difference between image enchantment and image restoration Image formation process and the degradation model Degradation model in continues function and its discrete formulation Discrete formulation for 1D and 2D 2 Todays lecture Estimation of Degradation Model By observation By experimentation Mathematical model Restoration techniques Inverse filtering 3 Degradation model 4 Estimation of Degradation Model Blind convolution operation By observation By experimentation Mathematical model 5 Degradation Model by observation 6 Example degraded image which has been cut out from a bigger degraded image. 7 Degradation Model by experimentation we try to get an imaging setup which is similar to the imaging setup before the degraded image. our purpose will be to find the impulse response of imaging setup. So, once the impulse response is known, the response of that system to any arbitrary input can be computed. So this means we need impulse simulation. 8 Impulse simulation How do you simulate an impulse? An impulse can be simulated by a very bright spot of light and because our imaging setup is a camera, so we will have a bright spot as small as possible of light falling on the camera, whatever image we get that is the response to that bright spot of light which in our case is an impulse. 9 Simulated impulse 10 simulated impulse Impulse response which is captured by the camera when this impulse falls on camera lens. Now, we know from our earlier discussion that for a narrow impulse, the Fourier transformation of an impulse is a constant. 11 Experimental setup We have got the degradation function through an experimental setup Is we have an imaging setup with a light source which can simulate an impulse. Using that impulse, we got an image which is the impulse response of this imaging system. We assume that the Fourier transform of the impulse is true as a constant A . | Digital Image Processing CSC331 Image restoration 1 Summery of previous lecture Image restoration techniques Difference between image enchantment and image restoration Image formation process and the degradation model Degradation model in continues function and its discrete formulation Discrete formulation for 1D and 2D 2 Todays lecture Estimation of Degradation Model By observation By experimentation Mathematical model Restoration techniques Inverse filtering 3 Degradation model 4 Estimation of Degradation Model Blind convolution operation By observation By experimentation Mathematical model 5 Degradation Model by observation 6 Example degraded image which has been cut out from a bigger degraded image. 7 Degradation Model by experimentation we try to get an imaging setup which is similar to the imaging setup before the degraded image. our purpose will be to find the impulse response of imaging setup. So, once the impulse response is known, the response of that system to any .