Image Processing Model Question

Section A

Attempt any two questions. (2 × 10 = 20)

1. Differentiate between Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT). Explain the FFT algorithm for one-dimensional case. [3+7=10]

2. Given the following frequency table obtained from the histogram of a 16 X 16, 8 level image.

M    0     1      2     3    4    5      6     7

N_M 15    6    70   16   31   35   32   51

Where M = gray level and NM = pixels having Mth gray level.

Construct Huffmann code for each gray level. Calculate the compression ratio and the relative data redundancy assuming if 3-bit code is used to code the gray level instead of Huffmann code. [7+3 =10]

3. What is an edge detection filter? Differentiate between the first derivative and second derivative filter? Derive the filter mask for laplacian filter and write the algorithm for its implementation. [1+2+7=10]

Section B

Attempt any eight questions. (8 × 5 = 40)

1.How many images of size 1024×768 with 256 gray levels can be stored in a 2048 MB storage space?

2. Write short notes on dilation and erosion.

3.Explain the contra-harmonic mean filters used in image restoration.

4.Explain the Bit plane slicing technique for image enhancement.

5.Explain how Hough transform is useful in line detection?

6.Describe in brief that how do you implement Gaussian High Pass Frequency domain filter for image smoothing in the frequency domain?

7. Explain lossy predictive coding in brief.

8. Explain the region growing technique for image segmentation.

9. Explain how can a neural network be applied in digital image processing with the help of a simple perceptron