Important questions from Unit-1: Digital Image Fundamentals for the image processing course. If you are preparing for AKTU or other university exams, these questions will guide you to understand the core concepts of image processing and help you in your exam preparations.
Table of Contents
Short Questions on Digital Image Fundamentals
1. What is digital image processing?
Hint: Digital image processing refers to the manipulation of digital images through algorithms. It involves enhancing, transforming, and extracting information from images to make them suitable for further analysis.
2. Explain gamma correction in image processing.
Hint: Gamma correction is used to adjust the brightness of an image. It compensates for the non-linear relationship between the intensity of light and the perceived brightness by the human eye.
3. Explain the relevance of DFT in image processing.
Hint: The Discrete Fourier Transform (DFT) is used to analyze the frequency components of an image. By transforming the image into the frequency domain, it becomes easier to filter or enhance images.
4. Explain the sampling and quantization of images with the help of a suitable diagram.
Hint: Sampling refers to selecting specific points from a continuous image to create a digital image, while quantization assigns discrete values to the intensity of those sampled points.
5. Explain the digital processing of camera images.
Hint: Digital processing of camera images involves converting the raw analog signal from a camera sensor into a digital form, followed by operations like enhancement, noise reduction, and feature extraction.
6. Draw the block diagram of digital image processing.
Hint: A block diagram typically includes stages like image acquisition, preprocessing, segmentation, feature extraction, and output generation.
7. Distinguish between sampling and quantization.
Hint: Sampling deals with selecting pixel positions in an image, while quantization refers to assigning specific values to the pixel intensities.
8. Draw the diagram and explain about the various components of an image processing system.
Hint: An image processing system consists of components like the input device (camera), processing unit (CPU), and output device (monitor), with algorithms performing operations on the image data.
9. Explain with the help of an example, sampling and quantization.
Hint: For example, in a grayscale image, sampling refers to selecting specific pixel locations, and quantization assigns a fixed intensity value to each pixel.
10. Obtain the digital negative of the following 8-bit per pixel image:
Hint: To get the digital negative of an image, subtract each pixel’s value from the maximum possible value (255 for an 8-bit image).
11. Explain sampling and quantization. Explain the effects of reducing sampling and quantization.
Hint: Reducing sampling results in lower resolution, while reducing quantization depth can cause loss of detail and introduce color banding.
12. What do you mean by image processing? Explain the steps in image processing with the help of a block diagram.
Hint: Image processing includes steps like acquisition, preprocessing, enhancement, segmentation, and interpretation. A block diagram represents these steps in a sequential flow.
13. What is digital image processing? Discuss some of its major applications.
Hint: Digital image processing involves techniques for enhancing or extracting information from images. Applications include medical imaging, satellite imaging, facial recognition, and image compression.
14. Consider two image subsets S1 & S2 as shown in the following figure. For V={0}, determine whether the regions are:
i) 4-adjacent
ii) 8-adjacent
iii) m-adjacent.
Give reason for your answer.
Hint: Pixel adjacency defines how pixels are connected. 4-adjacency connects pixels vertically and horizontally, 8-adjacency includes diagonals, and m-adjacency generalizes this.
15. Describe in detail the elements of a digital image processing system and describe sampling and quantization.
Hint: The system includes hardware (input/output devices), algorithms for processing, and a storage unit. Sampling and quantization are crucial steps to convert an image into a digital format.
16. Describe quantization in short.
Hint: Quantization is the process of mapping a continuous range of pixel intensities to a smaller, discrete set of intensity levels.
17. What is digital image processing? Describe in short.
Hint: Digital image processing is the manipulation of digital images to enhance their quality or extract useful information for analysis.
18. Describe gamma correction.
Hint: Gamma correction is used to adjust the brightness of an image to match the way humans perceive light, compensating for nonlinearities in display systems.
Long Questions on Digital Image Fundamentals
1. Explain the 4-8 and m connectivity of pixels. Explain region, edge in context with connectivity of pixels.
Hint: Pixel connectivity describes how pixels are linked together in an image. 4-connectivity links pixels horizontally and vertically, 8-connectivity also includes diagonal connections, and m-connectivity generalizes this concept.
2. Find the DFT of .
Hint: To find the DFT, apply the formula for the Discrete Fourier Transform to the given sequence. The DFT helps to analyze the frequency components of the sequence.
3. Given as follows, discuss its frequency response.
Hint: The frequency response of a filter shows how it affects different frequency components of an image. Analyzing it reveals the filter's impact on the image in the frequency domain.
4. What do you understand by digital image processing? Explain the components of an image processing system.
Hint: Digital image processing is the manipulation of images using algorithms. The components of the system include hardware (camera, processor) and software (image processing algorithms).
5. Extract the connected component from the following image.
Hint: Connected components are groups of adjacent pixels with similar intensity values. Use algorithms like flood-fill to extract and analyze these components.
6. Prove that 2-D continuous and discrete Fourier transforms are linear operations.
Hint: Linearity is a property of Fourier transforms where the transform of a sum of functions is the sum of the transforms. This can be shown mathematically.
7. Explain the steps involved in sampling and digitization of images. How many minutes are required for a 512*512 image with 256 grey levels at a 300 baud rate of transmission?
Hint: Sampling selects discrete points, and quantization assigns discrete values. Transmission time can be calculated based on the number of bits per pixel, baud rate, and the image size.
8. Describe any one image sharpening method in detail.
Hint: Methods like the Laplacian filter sharpen an image by highlighting rapid changes in intensity, making edges more defined.
9. Explain the HSI color model. Discuss image smoothing too.
Hint: The HSI color model represents colors based on Hue, Saturation, and Intensity. Image smoothing techniques reduce noise and fine details to make an image appear softer.
10. Explain the flow diagram of image analysis and understanding methods.
Hint: Image analysis involves steps like feature extraction, classification, and interpretation. The flow diagram helps visualize the step-by-step process of analyzing and understanding an image.
11. Explain sampling and quantization and differentiate them. Also, explain aliasing in the context of image sampling.
Hint: Sampling captures pixel locations, quantization represents pixel intensity with discrete values, and aliasing occurs when the sampling rate is too low to capture the image details properly.
12. Illustrate color models. Explain in detail how color models are converted to each other.
Hint: Color models like RGB and HSI represent colors in different ways. Conversion between models involves mathematical transformations based on their components.
13. Derive the expression for the second derivative of image sharpening (i.e., Laplacian filter).
Hint: The second derivative, like the Laplacian, helps enhance edges and fine details in an image by highlighting areas where intensity changes rapidly.
14. What do you mean by image processing? Explain the steps of image processing with the help of a block diagram.
Hint: Image processing involves steps such as acquisition, enhancement, segmentation, and interpretation. A block diagram represents these stages in a sequential flow.
15. Explain low-level, mid-level, and high-level processing. Also, explain sampling and quantization processes.
Hint: Low-level processing includes tasks like filtering, mid-level processing involves feature extraction, and high-level processing includes tasks like object recognition.
16. Differentiate correlation and convolution with a 1-D function and filter example.
Hint: Correlation and convolution are similar operations used in image processing, but convolution involves flipping the filter, while correlation does not.
Conclusion: Mastering Digital Image Fundamentals
These questions cover the essential concepts of Digital Image Fundamentals and are crucial for exam preparation. Understanding these concepts will give you a solid foundation in image processing. Best of luck with your studies!
