# 2007 Anna University Chennai B.E Biomedical Engineering DIGITAL IMAGE PROCESSING Question paper

** University Question Papers **

**
**2007 Anna University Chennai B.E Biomedical Engineering DIGITAL IMAGE PROCESSING Question paper

B.E. BIOMEDICAL ENGINEERING

DIGITAL IMAGE PROCESSING

MAX :100

ANSWER THE FOLLOWING:

PART A-(10*2=20)

1. What is known as Weber Ratio?

2. Illustrate the cause for false conforming in images.

3. Define Mach band effect.

4. Write the Hadamard transform matrix Hn for n=3.

5. Define the sine transform pair of 1D sequence.

6. What is meant by the Histogram of a digital image?

7. What are called median Filters?

8. Distinguish between image enhancement and image restoration

9. Mention the significant features of wavelet transform.

10. What is known as bit plane coding?

PART B-(5*16=80)

11. (a). Describe in detail the elements of digital image processing system .& write note on Non uniform sampling and Quantization.

(Or)

(b) . Discuss in detail the process of uniform sampling and quantization & illustrate the concept of brightness adaptation

12. (a).Explain in detail the properties of 2D DFT.(or)

(b) Discuss the salient features of Discrete Cosine transform Define the NXN Slant transform matrix and the various parameters.

13. (a) Describe the concept of Histogram specifications and Histogram modification for image enhancement & discuss the role of nonlinear filters in image enhancement.

(Or)

(b) Describe the principle of Homo-morphic filtering in image enhancement and Explain any one method pseudo collor image processing.

14. (a). Explain Huffman coding with an example and mention its salient features.& Describe the lossless predictive coding of images.

(Or)

(b). Explain the principle of Block truncation coding. & Describe the principle of wiener filtering in image Restoration.

15. (a). Explain the mathematical model of image degradation process & Describe the arithmetic coding of images with an example.

(Or)

(b). Discuss the image restoration process in linear algebraic approach. & and Describe the principle of Bayes classifier for pattern classification.