3) The aim of this project is to reduce the amount of noise in the image by image averaging technique. a) Use imnoise function in MATLAB and contaminate an input image with Gaussian noise with the same variance. Utilize image averaging technique and report the results for different noise variances. How many images are needed to be averaged to produce a low noise image for a given noise? ((Hint: consider the tradeoff between noise removal and edge blurring) b) Repeat part (a) but contaminate the input image with Gaussian noise with different variances. What do you conclude from Comparison the results of part (a) and (b)? c) Use imnoise function in MATLAB and contaminate an input image with salt-and-pepper noise. Utilize image averaging technique. Is this an effective method for salt-and-pepper noise reduction? d) Use medfilt2 function in MATLAB to implement median filter instead of average filter. Report the results.
3) The aim of this project is to reduce the amount of noise in the image by image averaging technique.
a) Use imnoise function in MATLAB and contaminate an input image with Gaussian noise with the same variance. Utilize image averaging technique and report the results for different noise variances. How many images are needed to be averaged to produce a low noise image for a given noise? ((Hint: consider the tradeoff between noise removal and edge blurring)
b) Repeat part (a) but contaminate the input image with Gaussian noise with different variances. What do you conclude from Comparison the results of part (a) and (b)?
c) Use imnoise function in MATLAB and contaminate an input image with salt-and-pepper noise. Utilize image averaging technique. Is this an effective method for salt-and-pepper noise reduction?
d) Use medfilt2 function in MATLAB to implement median filter instead of average filter. Report the results.
Trending now
This is a popular solution!
Step by step
Solved in 3 steps
