1. What is the primary purpose of High-Boost Filtering in image processing?
(A) Image compression
(B) Noise removal
(C) Edge enhancement
(D) Color correction
2. High-Boost Filtering is a generalization of which filtering technique?
(A) Median filtering
(B) Low-pass filtering
(C) High-pass filtering
(D) Gaussian filtering
3. Which of the following is enhanced by High-Boost Filtering?
(A) Image background
(B) Noise only
(C) Fine details and edges
(D) Low frequencies
4. In High-Boost Filtering, the original image is multiplied by which factor?
(A) 0
(B) 1
(C) A boost constant greater than 1
(D) Negative value
5. The high-boost filtered image is obtained by adding which component to the original image?
(A) Smoothed image
(B) Noisy image
(C) High-frequency components
(D) Median-filtered image
6. High-Boost Filtering can be mathematically represented as:
(A) A + A – L(A)
(B) A – L(A)
(C) L(A) – A
(D) A + H(A)
7. What does ‘A’ represent in the equation for high-boost filtering: A + k(A – L(A))?
(A) The blurred image
(B) The image mask
(C) The original image
(D) The filter kernel
8. In the formula A + k(A – L(A)), what does k control?
(A) Image resolution
(B) Boosting strength
(C) Compression ratio
(D) Filter size
9. What happens if the boost factor k = 1 in high-boost filtering?
(A) It behaves as a smoothing filter
(B) It behaves as a Laplacian filter
(C) It becomes a high-pass filter
(D) It becomes a low-pass filter
10. When k > 1 in High-Boost Filtering, the result is:
(A) No enhancement
(B) Suppression of high-frequency details
(C) Enhancement of high-frequency details
(D) Image blurring
11. What is the main drawback of increasing the boost factor excessively in high-boost filtering?
(A) Enhanced clarity
(B) Loss of contrast
(C) Amplification of noise
(D) Reduced sharpness
12. High-Boost Filtering improves which frequency components of an image?
(A) Low-frequency
(B) High-frequency
(C) Zero-frequency
(D) Mid-frequency
13. The high-frequency components in High-Boost Filtering are extracted using:
(A) Median filters
(B) Averaging filters
(C) Low-pass filters
(D) Subtraction of low-pass from original
14. Which type of images benefit the most from High-Boost Filtering?
(A) Cartoon images
(B) Medical images
(C) Smooth gradient images
(D) Satellite images with fine details
15. High-Boost Filtering is commonly used to:
(A) Remove impulse noise
(B) Blur edges
(C) Enhance blurred images
(D) Lower image resolution
16. Which component is subtracted from the original image to obtain detail in high-boost filtering?
(A) Laplacian image
(B) Median filtered version
(C) Low-pass filtered image
(D) Histogram equalized image
17. The process A – L(A) is known as:
(A) Low-boost filtering
(B) Edge detection
(C) High-pass filtering
(D) Histogram shifting
18. What effect does high-boost filtering have on image contrast?
(A) Always reduces it
(B) Enhances it locally
(C) Keeps it constant
(D) Only affects brightness
19. In image sharpening, high-boost filtering is preferred when:
(A) The image is already sharp
(B) Low-frequency enhancement is needed
(C) Edges are not prominent
(D) Histogram is skewed
20. What does the term “boost” in high-boost filtering refer to?
(A) Brightness correction
(B) Frequency shifting
(C) Emphasizing details
(D) Down-sampling
21. Which domain does high-boost filtering typically operate in?
(A) Frequency domain
(B) Time domain
(C) Spatial domain
(D) Compressed domain
22. The mask for high-boost filtering resembles that of:
(A) Sobel filter
(B) Gaussian filter
(C) Laplacian filter
(D) High-pass filter with a scaling factor
23. Which filter operation is most similar to high-boost filtering?
(A) Histogram equalization
(B) Low-pass filtering
(C) Unsharp masking
(D) Gamma correction
24. High-boost filtering is essentially:
(A) Amplified low-pass filtering
(B) Scaled unsharp masking
(C) Clipped histogram stretching
(D) Adaptive median filtering
25. A high-boost filter mask has which type of values at the center?
(A) Negative
(B) Zero
(C) Large positive
(D) Small positive
26. The size of the high-boost filter kernel affects:
(A) File size
(B) Processing time only
(C) Degree of detail enhancement
(D) Compression ratio
27. Which filtering technique is often used before high-boost filtering to suppress noise?
(A) Histogram equalization
(B) Gaussian smoothing
(C) Contrast stretching
(D) Sharpening
28. A boost constant of 2 in high-boost filtering implies:
(A) No enhancement
(B) Basic sharpening
(C) High sharpening
(D) Image smoothing
29. Which part of the image is mostly preserved in high-boost filtering?
(A) Uniform background
(B) Fine edges and lines
(C) Smooth gradients
(D) Flat regions
30. What kind of images may show artifacts after high-boost filtering?
(A) Well-lit images
(B) Noisy images
(C) Color-corrected images
(D) Scanned documents
31. High-boost filtering can cause ringing artifacts due to:
(A) Blurring
(B) Large kernel size
(C) Undersampling
(D) Excessive detail removal
32. Which technique is usually avoided when high-boost filtering is applied?
(A) Smoothing before filtering
(B) Histogram normalization
(C) Applying further sharpening
(D) Low-pass filtering
33. In practical applications, high-boost filtering is used for:
(A) Morphological operations
(B) Noise addition
(C) Enhancing scanned documents
(D) Blurring photos
34. High-boost filtering is sensitive to:
(A) Image dimensions
(B) Histogram shape
(C) Noise and boost factor
(D) Bit depth only
35. Boost factor ‘k’ is chosen based on:
(A) Filter type
(B) Desired level of detail enhancement
(C) Kernel size only
(D) Number of color channels
36. High-boost filtering is mostly effective in which processing tasks?
(A) Noise estimation
(B) Edge sharpening
(C) Image resizing
(D) Color balancing
37. In high-boost filtering, the filtered image is a combination of:
(A) Low-pass + median
(B) Original + high-pass
(C) Histogram + gradient
(D) Original – blurred
38. One limitation of high-boost filtering is:
(A) Color distortion
(B) Data loss
(C) Emphasis of unwanted features
(D) Excessive compression
39. Which value of boost constant ‘k’ provides no enhancement?
(A) 0
(B) 1
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(D) <1
40. High-boost filtering is conceptually a general case of:
(A) Laplacian enhancement
(B) Low-pass filtering
(C) High-pass filtering
(D) Unsharp masking
41. Which type of images should not be processed using high-boost filters without pre-processing?
(A) Denoised images
(B) Blurred grayscale images
(C) Noisy images
(D) High-contrast images
42. Which is not a feature of high-boost filtering?
(A) Enhances details
(B) Highlights edges
(C) Reduces resolution
(D) Increases contrast locally
43. What does L(A) represent in the high-boost formula A + k(A – L(A))?
(A) Original image
(B) Low-pass version of image
(C) High-frequency noise
(D) Sharpened image
44. Which application is most suitable for High-Boost Filtering?
(A) Motion tracking
(B) Background removal
(C) Text enhancement in scanned images
(D) Color segmentation
45. What is the visual effect of increasing the boost factor ‘k’ too much?
(A) Darkening of the image
(B) Loss of texture
(C) Over-sharpening and noise amplification
(D) Smoothing of the image
46. Which is a necessary step before applying high-boost filtering on noisy images?
(A) Histogram equalization
(B) Smoothing or denoising
(C) Resizing the image
(D) Applying thresholding
47. Which kernel center value is most likely in a 3×3 high-boost filter with k = 2?
(A) 1
(B) 9
(C) 5
(D) 8
48. High-Boost Filtering can be applied repeatedly to:
(A) Blur the image gradually
(B) Restore low-resolution images
(C) Sharpen images progressively
(D) Change image histogram
49. Which of the following is not directly associated with high-boost filtering?
(A) Edge enhancement
(B) Fine detail sharpening
(C) Noise suppression
(D) High-frequency emphasis
50. Which statement best defines High-Boost Filtering in image processing?
(A) A smoothing technique to reduce edges
(B) A sharpening method that enhances fine details by boosting high-frequency components
(C) A segmentation approach for object detection
(D) A contrast adjustment technique for color images
