Question 1

What is the difference between spatial domain and frequency domain in image p…

Accepted Answer

The spatial domain manipulates raw pixel coordinates directly, whereas the frequency domain violently transforms the image into a mathematical spectrum of sinusoidal frequencies.

Question 2

Define spatial resolution and gray-level resolution.

Accepted Answer

Spatial resolution defines the physical pixel density, while gray-level resolution dictates the absolute mathematical number of distinct shades available per pixel.

Question 3

What is a median filter? When is it used?

Accepted Answer

A Median Filter is a strict non-linear spatial algorithm that violently eradicates "salt-and-pepper" impulse noise without mathematically destroying structural edges.

Question 4

Explain the concept of an image histogram.

Accepted Answer

An image histogram is a strict mathematical probability density function graphically mapping the absolute frequency of every single intensity level in the image.

Question 5

What is a low pass filter and high pass filter in image processing?

Accepted Answer

A Low Pass Filter mathematically obliterates high frequencies to aggressively blur an image, while a High Pass Filter annihilates low frequencies to violently extract edges.

Question 6

Define the RGB and HSI color models.

Accepted Answer

RGB is an additive hardware architecture based on Red, Green, and Blue, while HSI is a psychological model isolating Hue, Saturation, and Intensity.

Question 7

What is thresholding in image segmentation?

Accepted Answer

Thresholding is a violent non-linear segmentation algorithm that mathematically binarizes an image by comparing every pixel to a strict intensity constant.

Question 8

Explain region growing.

Accepted Answer

Region Growing is a highly aggressive iterative segmentation algorithm that mathematically fuses adjacent pixels into a unified region based on strict similarity criteria.

Question 9

What is run-length coding?

Accepted Answer

Run-Length Coding (RLC) is a lossless mathematical compression architecture that violently collapses contiguous identical pixels into a single (value, length) pair.

Question 10

Define erosion and dilation in morphological processing.

Accepted Answer

Erosion mathematically shrinks image objects by violently stripping boundary pixels, while Dilation aggressively expands objects by mathematically adding boundary pixels using a structural element.

Question 11

Describe the process of image sampling and quantization in detail.

Accepted Answer

An exhaustive architectural breakdown of Image Digitization, detailing how spatial continuous coordinates are mathematically forced into a grid (Sampling) and how continuous voltage amplitudes are violently compressed into discrete binary levels (Quantization).

Question 12

Explain spatial domain filters for image enhancement.

Accepted Answer

A rigorous theoretical analysis of Spatial Domain Filters. Contrasts the linear mathematical convolution of Mean filters against the non-linear, noise-annihilating sorting algorithms of Median and Order-Statistic filters.

Question 13

Discuss the Fast Fourier Transform (FFT) and its application in image filtering.

Accepted Answer

An advanced mathematical breakdown of the Fast Fourier Transform (FFT). Details how the $O(N \log N)$ architecture shatters the image into orthogonal sinusoidal frequencies, allowing for absolute precision high/low-pass manipulation.

Question 14

Explain global thresholding for image segmentation.

Accepted Answer

A detailed exploration of Global Thresholding. Explains how a single mathematical constant violently segments the entire image array into absolute binary classes (Foreground and Background) based on the image histogram.

Question 15

Describe the wiener filtering approach for image restoration.

Accepted Answer

A rigorous theoretical review of the Wiener Filter. Details how this optimal linear filter mathematically balances Inverse Filtering and noise smoothing by aggressively minimizing the Mean Square Error between the estimated and original image.

Question 16

Discuss the CMY and HSI color models and their applications.

Accepted Answer

A definitive comparison of color models. Contrasts the CMY subtractive architecture utilized strictly in physical printing hardware against the HSI psychological model used for advanced mathematical image processing.

Question 17

Explain the use of morphological algorithms for boundary extraction.

Accepted Answer

An algorithmic review of morphological boundary extraction. Explains how applying mathematical Erosion with a structuring element, followed by set subtraction, violently exposes the exact perimeter of binary objects.

Question 18

Explain the concept of color image processing. Discuss different color models…

Accepted Answer

A massive architectural exposition on Color Image Processing. Violently details Full-Color processing mechanics across RGB/HSI models, and rigorously explains the mathematical assignment of false colors to grayscale data in Pseudo-Color architectures.

Question 19

Write detailed notes on: (a) Histogram Processing (b) Homomorphic filtering.

Accepted Answer

An exhaustive theoretical breakdown of Histogram Processing (Equalization and Matching) for mathematical contrast optimization, followed by a rigorous analysis of Homomorphic Filtering for eradicating catastrophic illumination gradients.

Question 20

Discuss the Hough Transform and its application in edge linking and boundary …

Accepted Answer

A deep technical exposition on the Hough Transform. Violently details the transformation from spatial $(x,y)$ coordinates to the mathematical $(ho, 	heta)$ parameter space to flawlessly detect disjointed lines and link broken edges in chaotic images.

Question 21

Explain various image compression models and discuss transform coding in detail.

Accepted Answer

A massive architectural review of Image Compression models. Violently contrasts spatial redundancy, psychovisual redundancy, and details the mathematically dominant Transform Coding architecture (DCT) utilized in the JPEG standard.

Question 22

Explain the steps involved in edge detection. Discuss the Canny edge detector…

Accepted Answer

A definitive theoretical breakdown of Edge Detection. Details the primitive mathematical gradient masks, and thoroughly dissects the massive multi-stage Canny Edge Detector architecture designed to achieve optimal, single-pixel perfect boundaries.

Digital Image Processing