IMAGE AND VIDEO PROCESSING

A gradient image's smallest possible value is:

1. 0
2. e
3. -e
4. 1

What equation do we use for the calculation of the B value according to the HSI components?

1. B=S(1-I)
2. B=I(1-S)
3. B=I(1+S)
4. B=S(1+I)

An alternate approach used in place of the median filtering is:

1. Sharpening
2. Laplacian filter
3. Gaussian filter
4. Using a mask

Image linear interpolation is given by the formula

1. v(x,y) = ax+by+cxy+d
2. v(x,y) = ax+by+cxy
3. v(x,y) = ax+by+d
4. v(x,y) = by+cxy+d

Value of plank's constant h is

1. 55x10^-34
2. 55x10^-34
3. 55x10^-34
4. 55x10^-34

DFT is applied to –

1. Infinite sequences
2. Finite discrete sequences
3. Continuous infinite signals
4. Continuous finite sequences

Which of the following fails to work on dark intensity distributions?

1. Laplacian Transform
2. Gaussian Transform
3. Histogram Equalization
4. Power-law Transformation

Decoder is used for –

1. Image Enhancement
2. Image Compression
3. Image Decompression
4. Image Equalization

In the formula 1-(1/C), C is the

1. Frame Rate
2. Compression Ratio
3. Constant
4. Conditional Ration

Which transformation represents shearing in the y-direction?

1. (x,y)→(x,y)
2. (x,y)→(x,y+a)
3. (x,y)→(x+ay,y)
4. (x,y)→(x,y+bx)

Explain the steps involved in the digitization of an image. How do sampling and quantization affect image quality?

Define the different types of relationships between pixels. Explain 4-neighborhood, 8-neighborhood, and m-connectivity with examples.

State and explain any five properties of 2-D DFT useful in image processing

For a 2×2 image f = [[1, 2], [3, 4]], compute the Hadamard Transform.

Explain Histogram Equalization. How does it enhance image contrast? Derive the transformation function.

Describe smoothing spatial filters. How does an averaging filter work? Provide a 3×3 example.

Compare RGB, CMY, and YIQ color models with respect to representation and applications.

Derive the Inverse Filter in the frequency domain. Why is it highly sensitive to noise?

Explain the three types of redundancies exploited in image compression: Coding, Spatial, and Temporal redundancy. Provide examples.

Construct a Huffman code for the following symbols and probabilities: A: 0.4, B: 0.2, C: 0.2, D: 0.1, E: 0.1

Given a 4×1 image: [10, 12, 13, 14], perform predictive coding using predictor: x̂(n) = x(n − 1)

Explain the differences between Analog Video and Digital Video. Discuss their advantages and limitations.

A camera captures 640×480 frames at 15 fps, 8 bits/pixel grayscale. Calculate storage needed for a 10-minute video.

Differentiate between Pixel-Based and Region-Based Motion Estimation.

Discrete cosine Transform

Lossy Vs Lossless Compression modals

Region-Based Motion Estimation

Run Length Coding