EC1009-Digital Image processing
Part A
1. What is Image Sampling and Quantization?
Sampling means digitizing the co-ordinate value (x, y).
Quantization means digitizing the amplitude value.
2. List out the properties of FFT
The FFT properties are
1. Separability
2. Translation
3. Periodicity and conjugate symmetry
4. Rotation
5. Distributivity and scaling
6. Average value
7. Laplacian
8. Convolution and correlation
9. Sampling
3. Compare the spatial and frequency domain Methods.
In spatial domain approach, the pixels of an image are manipulated directly.
Frequency domain approach is mainly based on modifying the Fourier
transform of an image.
4. What are the effects of applying Butterworth filter to a noisy image?
The transfer function of a Butterworth low pass filter of order n and with cut of
frequency at a distance D0 from the origin is,
Where D(u,v) = [(u . M/2) + (v-N/2) ]
It reduces the spurious effect on the noisy image.
5. Draw the model of Image degradation System.
Noise n(x,y)
Image f(x,y) Degraded image g(x,y)
6. Define pseudo Inverse with an example.
It is the stabilized version of the inverse filter.For a linear shift invariant system
with frequency response H(u,v) the pseudo inverse filter is defined as
= 0 for H=0
7. What is inter pixel redundancy?
The value of any given pixel can be predicted from the values of its neighbors.
The information carried by is small. Therefore the visual contribution of a single pixel to
an image is redundant. Otherwise called as spatial redundant geometric redundant or
inter pixel redundant. Eg: Run length coding
8. How sub image size selection affect transform coding?
The sub image size selection is one of the most important factor that affects the
transform coding error and computational complexity. The level of compression and
computation increases as the sub image size increase.
9. How edge detection is used for detecting discontinuities in a image?
An edge is a boundary between two regions with relatively distinct gray levels
properties. The magnitude of the first derivative is used to detect the presence of a edge
in the image and the sign of the second derivative is used to determine whether the edge
pixel lies on the darker side or lighter side of an edge.
10 Name the approaches used to describe texture.
Texture is one of the regional descriptors. It provides measures of properties such
as smoothness, coarseness and regularity. There are 3 approaches used to describe texture
of a region. They are
· Statistical
· Structural
· Spectral
PART B
11. a) Explain the elements of digital Image processing system with a neat diagram.
1. Image acquisition
2. Preprocessing
3. Segmentation
4. Representation and description
5. Recongniton and Interpretation
6. Knowledge base
(or)
b) Write a detailed note on:
(i) Walsh Transform (8)
The Walsh transform is defined by
Where --------------1-D forward Walsh Kernel
The 1-D inverse Walsh transform is expressed as
Where --------------1-D Inverse Walsh Kernel
Discrete cosine Transform (8)
12. a) Discuss in detail Histogram Processing of a digital Image.
(or)
b) Write a detailed note on image enhancement in the frequency domain.
Low pass Filtering
High pass Filtering
13. a) What is image restoration? Explain the degradation model for continuous function
in detail.
(or)
b) Discuss about constrained least square restoration of a digital image.
14. a) Explain the image Compression models in detail.
Lossless Compression and Lossy compression.
Explain different types of compression models for three types of redundancies
(or)
b) Differentiate between lossless and lossy compression and explain transform
coding system with a diagram.
| Lossless predictive coding | Lossy predictive coding |
| 1. No loss of image information 2. Quantizer is not available 3. Less Compression is achieved | 1. Lossy compression method 2. Quantizer is used 3. High compression is achieved with loss of image information |
Transform coding
Block diagram of transform coding
Write about coding using 2-D DFT, DCT and Walsh transform
15. a) Explain the concept of Thresholding in image segmentation and discuss their
merits and limitation.
Bilevel Thresholding, Multilevel Thresholding
Global Thresholding
Local Thresholding
Dynamic and adaptive thresholding
(or)
b) Explain the boundary descriptors in detail with a neat diagram.
(i) Simple descriptors
i. Length
ii. Diameter
iii. Major axis, Minor axis
iv. Eccentricity
v. Basic Rectangle
vi. Curvature
(ii) Fourier Descriptors
(iii) Statistical moments
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