Image Processing Important Questions

BCA Seventh Semester Image Processing Important Questions For Exam Preparations

Unit 1: Fundamentals of Image Processing

1. Define Digital Image Processing (DIP) and explain the elements of a DIP system with a neat diagram.
2. Explain image representation and basic relationships between pixels (neighbors, adjacency, connectivity).
3. Describe the simple image formation model and elements of visual perception.
4. Explain sampling and quantization.
   • Numerical: Calculate image size for given resolution and color levels (e.g., 512 colors, 1028×1028 image).
5. Explain color fundamentals and compare RGB, CMY, HSI color models.
6. Explain different image file formats (BMP, JPEG, PNG, TIFF).
7. Explain image operations: brightness, contrast, hue, and saturation.
8. Explain the Mach Band Effect with diagram and significance.

Unit 2: Image Enhancement

1. Define Fourier Transform (FT) and Discrete Fourier Transform (DFT).
2. Prove that 2-D Continuous and Discrete Fourier Transforms are linear operations.
3. Explain Fast Fourier Transform (FFT) and its advantages.
4. Explain Cosine Transform (DCT) and its applications.
5. Explain low pass, high pass, band pass filters in frequency domain.
6. Define Ideal, Butterworth, and Gaussian filters.
   • When does Butterworth LPF become Ideal LPF?

7. Explain point processing techniques.
8. Explain contrast stretching, clipping, and thresholding.
9. Explain digital negative and intensity level slicing.
10. Explain histogram processing:
    • Histogram equalization
    • Histogram modification
    • Numerical problem on histogram equalization
11. Explain spatial filtering:
    • Averaging
    • Smoothing
    • Sharpening
    • Median filtering

Unit 3: Image Restoration

1. Differentiate between Image Enhancement and Image Restoration.
2. Explain the image degradation model with diagram.
3. Explain different noise models:
   • Gaussian noise
   • Salt and pepper noise
   • Suggest suitable filters for each
4. Explain blur model and causes of blur.
5. Explain inverse filtering.
6. Explain removal of blur caused by uniform linear motion.
7. Explain Wiener filtering and its advantages.
8. Explain morphological operations:
   • Erosion
   • Dilation
   • Applications

Unit 4: Image Coding and Compression

1. Explain the need for image compression.
2. Explain types of redundancy in images.
3. Explain pixel coding.
4. Explain Run Length Coding (RLC) with example.
5. Explain Huffman Coding with example.
6. Explain elements of information theory related to image compression.
7. Differentiate between lossless and lossy compression.
8. Explain JPEG compression standard.
9. Explain MPEG compression standard.
10. Explain wavelet-based image compression.
11. Draw and explain the functional block diagram of an image compression system.

Unit 5: Image Segmentation & Feature Extraction

1. Define image segmentation and its importance.
2. Explain thresholding techniques.
3. Explain region growing with example.
4. Explain region splitting and merging.
5. Explain edge detection.
6. Explain edge operators (Sobel, Prewitt, Roberts, Canny).
7. Explain line and curve detection.

8. Define image features.
9. Explain types of features (shape, texture, color).
10. Explain feature extraction process.
11. Explain texture analysis.
12. Explain feature reduction algorithms.
13. Explain image classification.
14. Explain clustering techniques used in image processing.

15. Case study on Image Security.
16. Explain Steganography.
17. Explain Digital Watermarking.
18. Case study on Medical Imaging.
19. Case study on Remote Sensing.
20. Explain visual effects in image processing.

Note: This list is for reference purposes only, to help you prepare smartly and cover all the critical areas. Always review your class notes, teacher guidelines, and syllabus coverage.

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