Classify the applications of imaging based on radiation from electromagnetic spectrum of source for imaging. Explain two examples of the X -ray imaging.

List out and explain three most commonly used probability distribution functions of noise models.

Difference between CWT and DWT.

What are the mathematical conditions for a signal to be considered as a wavelet?

How to make wavelet more flexible to use it in signal analysis

Define mother and daughter wavelets.

Develop an algorithm for converting one-pixel-thick 8-path to a 4-path.

Explain the advantages with the help of an example.

Write an algorithmic procedure to implement a filter for reduction of the blurring and noise for image enhancement.

Provide one example where filtering is not preferred.

5. Image subtraction is often used in industrial applications for detecting missing components in product assembly. The approach is to store a golden image that corresponds to a correct assembly; this image is then subtracted from incoming images of the same product. Ideally, the differences would be zero if the new products are assembled correctly. Difference images for products with missing components would be non zero in the area where they differ from the golden image.

What conditions do you think have to be met in practice for this method to work?

Explain the arithmetic, geometric, and harmonic mean filters used for image restoration.

Give the merits and demerits of these three mean filters.

Compare mean filters with median filters.

What are the various types of thresholding techniques

Explain how is the denoising of a signal done using wavelets with thresholding.

8. Classify any two wavelet families with the help of their mathematical formulas and properties.