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Introduction to Digital Image Processing – MCQs

1. Q1: What is the basic unit of a digital image?

(A) Dot


(B) Pixel


(C) Voxel


(D) Bit



2. Q2: Digital Image Processing primarily deals with ___.

(A) Analog signals


(B) Discrete signals


(C) Continuous signals


(D) Mixed signals



3. Q3: The process of converting an analog image into digital form is called ___.

(A) Scanning


(B) Quantization


(C) Sampling


(D) Digitization



4. Q4: The number of bits used to represent each pixel is known as ___.

(A) Bit Plane


(B) Bit Depth


(C) Resolution


(D) Byte Level



5. Q5: The device used to acquire digital images is known as ___.

(A) Scanner


(B) Sensor


(C) Camera


(D) All of the above



6. Q6: Which of the following defines image resolution?

(A) File size


(B) Bit depth


(C) Number of pixels


(D) Image color



7. Q7: Which image transformation is used to enhance contrast?

(A) Image subtraction


(B) Log transformation


(C) Histogram equalization


(D) Bit-plane slicing



8. Q8: Image noise is generally caused by ___.

(A) Sensor temperature


(B) Transmission errors


(C) Illumination conditions


(D) All of the above



9. Q9: What does HVS stand for in image processing?

(A) Human View System


(B) Human Vision System


(C) High Visual Sensitivity


(D) Horizontal View Segment



10. Q10: The process of adjusting the image to enhance its quality is called ___.

(A) Image enhancement


(B) Image segmentation


(C) Image recognition


(D) Image conversion



11. Q11: Which function is used to reduce image size without losing details?

(A) Enlargement


(B) Decimation


(C) Smoothing


(D) Cropping



12. Q12: A grayscale image typically has how many intensity levels?

(A) 16


(B) 64


(C) 128


(D) 256



13. Q13: Which color model is commonly used in digital image processing?

(A) RGB


(B) CMYK


(C) HSV


(D) YCbCr



14. Q14: The operation that combines two images by adding their pixel values is called ___.

(A) Image blending


(B) Image addition


(C) Image filtering


(D) Image fusion



15. Q15: What is the purpose of image quantization?

(A) To resize image


(B) To reduce noise


(C) To assign gray levels


(D) To increase resolution



16. Q16: Power-law transformation is also called ___.

(A) Contrast stretching


(B) Log transformation


(C) Gamma correction


(D) Smoothing



17. Q17: Which technique is used to remove high-frequency noise?

(A) High-pass filter


(B) Edge detection


(C) Low-pass filter


(D) Histogram equalization



18. Q18: Bit-plane slicing is used to ___.

(A) Compress images


(B) Isolate significant bit information


(C) Improve contrast


(D) Add filters



19. Q19: Which method enhances an image by spreading out its intensity values?

(A) Image subtraction


(B) Histogram specification


(C) Histogram equalization


(D) Image sharpening



20. Q20: What is the main disadvantage of increasing bit depth?

(A) Lower resolution


(B) Lower contrast


(C) Higher memory usage


(D) Blurred image



21. Q21: An image with more pixels per inch is said to have higher ___.

(A) Bit depth


(B) Resolution


(C) Color depth


(D) Compression



22. Q22: Which of the following is not an image enhancement technique?

(A) Log transformation


(B) Contrast stretching


(C) Histogram equalization


(D) Compression



23. Q23: Which transform is used in frequency domain processing?

(A) Histogram


(B) Fourier Transform


(C) Bit slicing


(D) Color inversion



24. Q24: What does DCT stand for in DIP?

(A) Digital Code Transformation


(B) Discrete Cosine Transform


(C) Digital Channel Testing


(D) Discrete Channel Transfer



25. Q25: What is the main goal of image segmentation?

(A) Resize the image


(B) Divide image into regions


(C) Compress the image


(D) Increase brightness



26. Q26: Which is used to sharpen an image?

(A) Low-pass filter


(B) Smoothing filter


(C) High-pass filter


(D) Histogram equalization



27. Q27: The technique of averaging pixel values is used in ___.

(A) Edge detection


(B) Sharpening


(C) Smoothing


(D) Segmentation



28. Q28: A binary image has how many intensity levels?

(A) 1


(B) 2


(C) 8


(D) 256



29. Q29: Which of the following enhances the edges in an image?

(A) Smoothing


(B) Median filter


(C) Laplacian operator


(D) Contrast stretching



30. Q30: Which filter is most effective in removing salt-and-pepper noise?

(A) Gaussian filter


(B) Median filter


(C) Mean filter


(D) Butterworth filter



31. Q31: In digital image processing, the spatial domain refers to ___.

(A) Frequency values


(B) Pixel location


(C) Intensity distribution


(D) Color mapping



32. Q32: The smallest addressable element in an image is a ___.

(A) Pixel


(B) Node


(C) Dot


(D) Grid



33. Q33: Image restoration aims to ___.

(A) Enhance the image


(B) Blur the image


(C) Recover degraded images


(D) Convert color models



34. Q34: A 3×3 mask is commonly used in ___.

(A) Filtering


(B) Color conversion


(C) Coding


(D) Resizing



35. Q35: What is the purpose of zero-padding?

(A) Increase contrast


(B) Avoid aliasing


(C) Enhance resolution


(D) Adjust filter size



36. Q36: Which of the following is a non-linear filter?

(A) Gaussian filter


(B) Laplacian filter


(C) Median filter


(D) Mean filter



37. Q37: Which of the following is used for edge detection?

(A) Sobel operator


(B) Gaussian blur


(C) Low-pass filter


(D) Inverse filter



38. Q38: In histogram equalization, the histogram is made ___.

(A) Narrow


(B) Steep


(C) Uniform


(D) Flat



39. Q39: In a color image, each pixel typically contains ___.

(A) One color value


(B) Two color values


(C) Three color values


(D) Four color values



40. Q40: A 24-bit image supports how many colors?

(A) 256


(B) 512


(C) 16,777,216


(D) 65,536



41. Q41: Which process reduces the size of image data?

(A) Enhancement


(B) Segmentation


(C) Compression


(D) Filtering



42. Q42: Which of the following can perform spatial smoothing?

(A) Laplacian


(B) Sobel


(C) Averaging filter


(D) Roberts



43. Q43: In negative transformation, pixel value r is transformed to:

(A) r + L – 1


(B) L – 1 – r


(C) L – r


(D) r – L



44. Q44: Log transformation is useful for ___.

(A) Brightening dark regions


(B) Edge detection


(C) Noise removal


(D) High-contrast regions



45. Q45: Which image representation uses continuous values?

(A) Digital image


(B) Binary image


(C) Analog image


(D) Grayscale image



46. Q46: A high-pass filter emphasizes ___.

(A) Low-frequency components


(B) High-frequency components


(C) Both


(D) None



47. Q47: What does PSNR stand for?

(A) Power Signal Noise Ratio


(B) Pixel Sensitivity and Noise Ratio


(C) Peak Signal-to-Noise Ratio


(D) Picture Size Normal Ratio



48. Q48: Which is not a basic image enhancement technique?

(A) Log transformation


(B) Histogram equalization


(C) Fourier transform


(D) Contrast stretching



49. Q49: What is the full form of DIP?

(A) Digital Information Processing


(B) Digital Image Programming


(C) Digital Image Processing


(D) Digital Input Processing



50. Q50: Which software is commonly used for image processing tasks?

(A) Photoshop


(B) MATLAB


(C) OpenCV


(D) All of the above



More MCQs on Digital image Processing

  1. Introduction to DIP — MCQs | Digital Image Processing

  2. Human Visual System (HVS) — MCQs | Digital Image Processing

  3. Image Acquisition Devices — MCQs | Digital Image Processing

  4. Image Sampling & Quantization — MCQs | Digital Image Processing

  5. Image Resolution & Bit Depth — MCQs | Digital Image Processing

  6. Basic Image Operations (Negative, Log, Power-law) — MCQs | Digital Image Processing

  7. Histogram Equalization & Specification — MCQs | Digital Image Processing

  8. Contrast Stretching — MCQs | Digital Image Processing

  9. Image Arithmetic (Add, Subtract, Multiply, Divide) — MCQs | Digital Image Processing

  10. Bit-plane Slicing — MCQs | Digital Image Processing

  11. Smoothing Filters (Mean, Gaussian, Median) — MCQs | Digital Image Processing

  12. Sharpening Filters (Laplacian, Gradient) — MCQs | Digital Image Processing

  13. High-Boost Filtering — MCQs | Digital Image Processing

  14. Edge Detection (Sobel, Prewitt, Roberts, Canny, LoG) — MCQs | Digital Image Processing

  15. Fourier Transform (DFT, FFT) — MCQs | Digital Image Processing

  16. Frequency Domain Filtering — MCQs | Digital Image Processing

  17. Low-pass & High-pass Filters — MCQs | Digital Image Processing

  18. Homomorphic Filtering — MCQs | Digital Image Processing

  19. Noise Models (Gaussian, Salt & Pepper, Speckle) — MCQs | Digital Image Processing

  20. Adaptive Filtering — MCQs | Digital Image Processing

  21. Inverse & Wiener Filtering — MCQs | Digital Image Processing

  22. Pseudo-color & True-color Processing — MCQs | Digital Image Processing

  23. Color Space Conversion (RGB ↔ HSV, HSI, YCbCr) — MCQs | Digital Image Processing

  24. Color Image Enhancement — MCQs | Digital Image Processing

  25. Image Segmentation (Thresholding, Otsu, K-means, Region Growing) — MCQs | Digital Image Processing

  26. Edge-based Segmentation — MCQs | Digital Image Processing

  27. Region Splitting and Merging — MCQs | Digital Image Processing

  28. Watershed Algorithm — MCQs | Digital Image Processing

  29. Morphological Operations (Erosion, Dilation, Opening, Closing) — MCQs | Digital Image Processing

  30. Boundary Extraction — MCQs | Digital Image Processing

  31. Skeletonization — MCQs | Digital Image Processing

  32. Connected Components Labeling — MCQs | Digital Image Processing

  33. Texture Analysis (GLCM, LBP, Gabor Filters) — MCQs | Digital Image Processing

  34. Shape Descriptors (Perimeter, Area, Compactness, Eccentricity) — MCQs | Digital Image Processing

  35. Statistical Features (Mean, Variance, Skewness) — MCQs | Digital Image Processing

  36. Principal Component Analysis (PCA) — MCQs | Digital Image Processing

  37. Linear Discriminant Analysis (LDA) — MCQs | Digital Image Processing

  38. Feature Matching (SIFT, SURF, ORB) — MCQs | Digital Image Processing

  39. Image Registration — MCQs | Digital Image Processing

  40. Image Stitching — MCQs | Digital Image Processing

  41. Motion Detection & Optical Flow — MCQs | Digital Image Processing

  42. Background Subtraction — MCQs | Digital Image Processing

  43. Object Detection & Tracking — MCQs | Digital Image Processing

  44. Template Matching — MCQs | Digital Image Processing

  45. Pattern Recognition (KNN, SVM, ANN) — MCQs | Digital Image Processing

  46. Image Classification — MCQs | Digital Image Processing

  47. Image Clustering — MCQs | Digital Image Processing

  48. Image Compression (RLE, Huffman, LZW, JPEG, JPEG2000) — MCQs | Digital Image Processing

  49. Video Compression (MPEG, H.264) — MCQs | Digital Image Processing

  50. Image Fusion (Pixel, Feature, Decision Level) — MCQs | Digital Image Processing

  51. Image Watermarking — MCQs | Digital Image Processing

  52. Steganography — MCQs | Digital Image Processing

  53. Face Detection & Recognition — MCQs | Digital Image Processing

  54. Gesture Recognition — MCQs | Digital Image Processing

  55. 3D Image Processing — MCQs | Digital Image Processing

  56. Stereo Vision & Depth Estimation — MCQs | Digital Image Processing

  57. Medical Image Analysis (CT, MRI, Ultrasound) — MCQs | Digital Image Processing

  58. Remote Sensing Image Processing — MCQs | Digital Image Processing

  59. Satellite Image Enhancement — MCQs | Digital Image Processing

  60. Deep Learning for Image Processing (CNN, GANs, Autoencoders) — MCQs | Digital Image Processing

  61. Image Captioning — MCQs | Digital Image Processing

  62. Semantic & Instance Segmentation (Mask R-CNN, U-Net) — MCQs | Digital Image Processing

  63. Super Resolution (SRCNN, ESRGAN) — MCQs | Digital Image Processing

  64. Image Inpainting — MCQs | Digital Image Processing

  65. Image Style Transfer — MCQs | Digital Image Processing

  66. Real-Time Image Processing — MCQs | Digital Image Processing

  67. Augmented Reality (AR) & Virtual Reality (VR) — MCQs | Digital Image Processing

  68. DIP using MATLAB/OpenCV/Python — MCQs | Digital Image Processing

  69. DIP in IoT & Embedded Systems — MCQs | Digital Image Processing

  70. Ethics & Privacy in Image Processing — MCQs | Digital Image Processing

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