Practice questions for second internal exam

Digital Image Processing

Practice questions for second internal exam

Unit-5 : Colour Image Processing

1. List the various color models that are used today. Justify their need.
2. Explain the RGB, CMY, CMYK, HIS and YCrCb color models in detail.
3. What is the need for HIS model ?  Explain with neat sketches how this model is related to the RGB model. Give suitable conversion formulae.
4. Provide the conversion formulae for representing a color in one model as a color in a different model.
5. Distinguish between pseudo color and full color.
6. Discuss the different methods used in pseudo color processing.
7. Discuss the different methods used in full color processing.

Unit -6 : Image restoration and reconstruction

1. How is image restoration different from image enhancement ?
2. With the help of an image degradation model explain the important causes that lead to image degradation. How can they be removed ?
3. Using detailed mathematical formulae and graphical representation explain in detail the various noise models that are used during image restoration.
4. How do you determine which noise model is applicable for a given situation ?
5. Explain the different types of spatial filters used to remove noise from a degraded image. Comment on their suitability.
6.  How are degradation functions estimated  ?  Discuss in detail.
7. Discuss the various inverse filtering schemes and bring out their relative merits and demerits.

Unit-7 : Image segmentation

1. What is segmentation ? Briefly explain the basis  on which it is done.
2. When is segmentation successful ? Explain with examples.
3. What is the role played by the first and second derivatives in detecting an edge ? Explain the relative merits and demerits of both.
4. Explain in detail how point, line and edge detection is done.
5. Classify edges using simple sketches. List the steps performed in edge detection ?
6. Discuss the role of masks in edge detection.
7. How does thresholding help in edge detection ? What is hysteresis thresholding ?
8. Explain the Marr-Hildreth edge detection process in detail.
9. Explain the Canny edge detection process in detail.

Unit – 8 : Image Compression

1. What are the objectives of image compression ?
2. What are the different means by which image compression can be achieved ?
3. Give examples of different types of redundancies that may exist in images.
4. Explain the basic concepts such as information, data, compression, mapping, channel coding, entropy, quantization , source coding, average length of a code, efficiency based on the foundation of information theory. Use formulae and examples wherever necessary.
5. What schemes will you propose to remove coding redundancy /spatial redundancy/ttemporal redundancy/irrelevant information ? Give examples.
6. Discuss the fidelity criteria to quantify loss of information. What care will you exercise while analyzing the results ?
7. With a neat sketch explain the image compression and decompression process. Explain the function (with examples) of each block in the system.
8. Problems based on the following compression algorithms : Huffman coding, Arithmetic coding, Lempel-Ziv-Welch coding.
9. Explain in detail the theory behind : Golomb coding, Block Transform Coding, JPEG coding , Predictive coding.

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