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03000EC370052104

Explain any four local neighbourhood operations used in image enhancement.
Explain the principle of inverse filtering. Give the drawbacks of inverse filtering.
Derive a Wiener filter for image restoration using minimum mean square
approach. Mention the situation in which the behaviour of Wiener filter
resembles that of inverse filter.

With diagram, explain the principle of different slicing techniques used in image
enhancement.

PART ட
Answer any two full questions, each carries 20 marks
Explain the need for image compression.

What is image segmentation? Explain the different thresholding techniques used
for image segmentation.

With diagram, explain vector quantization.

What are the different types of edges present in an image? Explain the two
approaches for detection of edges in an image.

Explain the different types of redundancy present in images.

Explain an image analysis tool for refinement of an object boundary.

Explain the role of Hough transform in edge linking.

A source emits 4 symbols {m, n, ௦, 0) with probabilities (0.1, 0.2, 0.3, 0.4}
respectively. Perform arithmetic coding to encode the word “pop”.

Explain K-means clustering.

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