Description
Q1. a. Find the convolution of ( , ) given by
- 3
- 5
With ( , ) given by
- 2
- 1
Origin is at top leftmost element for both. | [2] |
- Write a program to compute this convolution and verify if both the results are in consensus. You can use built in
functions. Refer to the lecture notes. | [2] | |||
Q2. Find the response of a 3×3 median filter on ( , ) given by | ||||
3 | 4 | 1 | ||
8 | 6 | 6 | ||
5 | 4 | 3 | ||
Assume zero padding at the borders. The first output should correspond to the response of the filter with center at
element 3 at top left. Similarly last response should be at bottom right 3. | [2] | ||||||||
Q3. a. Perform histogram equalization (HE). Assume bit depth to be 2. | [1] | ||||||||
r | p(r) | z | p(z) | ||||||
0 | 0.8 | 1 | 0.3 | ||||||
1 | 0.2 | 2 | 0.7 | ||||||
Give the output pixel values. | |||||||||
b. Write a code to perform HE for part a. You can refer to the lecture notes. | [2] | ||||||||
Q4. In a local/adaptive processing for a 4×4 image given by | [1] | ||||||||
3 | 3 | 0 | 0 | ||||||
3 | 3 | 0 | 1 | ||||||
1 | 0 | 1 | 0 | ||||||
0 | 0 | 0 | 1 | ||||||
Considering the global image to be 4×4, the mean is 1 and variance is 3/2. Consider the 2×2 local window in red color. Compute its mean and variance. Suppose you want to enhance the intensity in this region, and use constraints
< | 2 | < 2 | , K >0, C > 0 | ||||||
( , ) = | { | ( , ) | When the constraints are satisfied | ||||||
( , ) | ℎ | ||||||||
, | , 2 | , 2 | , | ||||||
( , ) , ( , ) , > 1
Find , .