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Tuesday, May 24, 2011

DIGITAL IMAGING PROCESSING ONE MARK

DIGITAL IMAGE PROCESSING

1. Preprocessing of an image is done in

image acquisition
image segmentation
image restoration
image enhancement

2. Which process is called subjective process?

image acquisition
image segmentation
image restoration
image enhancement

3. Which process is called an objective process?

image compression
image segmentation
image restoration
image enhancement

4. Which process split an input image into its constituent parts

image acquisition
image segmentation
image restoration
image enhancement

Which process involves the mathematical or probabilistic methods in its operation

image acquisition
image segmentation
image restoration
image enhancement

6. Which process is used in improving image contrast?

image acquisition
image segmentation
image restoration
image enhancement

7. Which Process is used in removal of optical distortions?

image acquisition
image segmentation
image restoration
image enhancement

8. Which technique is used for reducing the storage required to save an image

image compression
image segmentation
image restoration
image enhancement

9. Which Process is used in sharpening or de-blurring an out of focus image?

image acquisition
image segmentation
image restoration
image enhancement

10. Which Process is used in removing periodic interference?

image acquisition
image segmentation
image restoration
image enhancement

11. Which process uses tools for extracting image components

Compression
Morphological Processing
Restoration.
Segmentation

12. Which Process involves removing of blur caused by linear motion?

image compression
image segmentation
image restoration
image enhancement

13. Which process transforms raw data into a form suitable for subsequent processing

Image Representation
Morphological Processing
Image Restoration
Image compression

14. Which process is also called feature selection?

Image Description
Morphological Processing
Image Restoration
Image Segmentation

15. Which is the process that assigns a label (e.g., “vehicle”) to an object based on its descriptors?

Image Description
Morphological Processing
Image Recognition
Image Segmentation

16. In each eye, cones are in the range of

6-7 million.
75-150 million
65-75 million
5-7 million

17. In each eye, rods are in the range of

6-7 million
75-150 million
65-75 million
5-7 million

18. Scotopic vision is also called as

Dim light vision
Bright light vision
Moderate vision
No vision

19. Photopic vision is also called as

Dim light vision
Bright light vision
Moderate vision
No vision

20. Cone vision is called as

Dim light vision
Bright light vision
Moderate vision
No vision

21. The observer is looking at a tree15 m high at a distance of 100 m , Calculate the height in mm of
that object in the retinal image

0.15 mm
2.55 mm
0.55 mm
6.66 mm

22. Weber Ratio is given by

∆i * i
∆i / i
i /∆i
i-∆i

23. The spatial interaction of Luminance from an object and its surround creates a phenomenon
called

Subjective brightness
Brightness adaptation
Mach band effect
Simultaneous Contrast

24. Intensity as preserved by the human visual system is called as

Subjective brightness
Brightness adaptation
Mach band effect
Simultaneous Contrast

25. Which operation increases the dynamic range of the gray levels in the image?

Subjective brightness
Brightness adaptation
Mach band effect
Contrast stretching

26. Digitizing the amplitude values is called

Quantization
Compression
Sampling
Restoration

27. Digitization of spatial coordinates (x,y) is called

Quantization
Compression
Sampling
Restoration

28. Which type of image is commonly used as a multiplier to mask regions within another image.

Binary images
Indexed Images
Gray scale image
RGB image

29. Find the number of bits required to store a M X N image with 2m gray levels?

M X N X m bits
m X N bits
M X N bits
m X M bits

30. Find the number of bits required to store a 256 X 256 image with 64 gray levels?

655360 bits
65536 bits
393216 bits
327680bits

31. Find the number of bits required to store a 512 X 512 RGB color image with 2 grey levels?

.786 MB
.262 MB
512 MB
1024 MB

32. The Euclidean distance between p and q is defined as

Max | ( x – s ) | , | ( y – t ) |
[( x – s )2 + ( y – t ) 2 ]
[( x – s )2 + ( y – t ) 2 ]1/2
|(x–s)|+|(y–t)|

33. Chess board (D8) distance is calculated by

Max | ( x – s ) | , | ( y – t ) |
[( x – s )2 + ( y – t ) 2 ]
[( x – s )2 + ( y – t ) 2 ]1/2
|(x–s)|+|(y–t)|

34. The effect of aliased frequencies can be seen under the right conditions in the form of so called

Moire Patterns
Brightness adaptation
Mach band effect
Simultaneous Contrast

35. City block (D4) distance is calculated by

Max | ( x – s ) | , | ( y – t ) |
[( x – s )2 + ( y – t ) 2 ]
[( x – s )2 + ( y – t ) 2 ]1/2
|(x–s)|+|(y–t)|

36. Give the relation for 1d DCT

1/N x=0∑N-1 f(x) exp [-j2πux/N]

α(u) x=0∑N-1f(x)cos[(2x+1)uπ/2N]

N −1



1/N

x =0

1/N

x=0∑ N-1 f(x) i=0

f(x) (-1) ∑i =0

Π n-1 (-1) bi (x) bn-1-I (u)

37. Give the relation for 1d DFT

1/N x=0∑N-1 f(x) exp [-j2πux/N]

α(u) x=0∑N-1f(x)cos[(2x+1)uπ/2N]

N −1



1/N

x =0

1/N

x=0∑ N-1 f(x) i=0

f(x) (-1) ∑i =0

Π n-1 (-1) bi (x) bn-1-I (u)

38. Give the relation for Hadamard Transform

1/N x=0∑N-1 f(x) exp [-j2πux/N]

α(u) x=0∑N-1f(x)cos[(2x+1)uπ/2N]

N −1

1/N



x =0

1/N

x=0∑ N-1 f(x) i=0

f(x) (-1) ∑i =0

Π n-1 (-1) bi (x) bn-1-I (u)

39. Give the relation for Walsh Transform

1/N x=0∑N-1 f(x) exp [-j2πux/N]

α(u) x=0∑N-1f(x)cos[(2x+1)uπ/2N]

N −1



1/N

x =0

1/N

x=0∑ N-1 f(x) i=0

f(x) (-1) ∑i =0

Π n-1 (-1) bi (x) bn-1-I (u)

40. Which model is used for color monitor & color video camera?

RGB model
CMY model
YIQ model
HIS model

41. Which model is used for color printing?

YIQ model
CMY model
HIS model
RGB model

42. Which model is used for color image processing?

RGB model
YIQ model
CMY model
HIS model

43. Which model is used for color picture transmission?

RGB model
YIQ model
HIS model
CMY model

44. Zooming of digital images may be viewed as

over sampling
under sampling
flat sampling
critical sampling

45. Shrinking of digital images may be viewed as

over sampling
under sampling
flat sampling
critical sampling

46. Give the Conditions for perfect transform

Transpose of matrix ! = Inverse of a matrix.
Transpose of matrix = ( inverse of a matrix )2
Transpose of matrix = Inverse of a matrix
Transpose of matrix = ( inverse of a matrix )1/2.

47. Which transform is called very fast transform?

HAAR Transform
HADAMARD Transform
SINE Transform
COSINE Transform

48. Which transform has very poor energy compaction for images?

COSINE Transform
HADAMARD Transform
SLANT Transform
HAAR Transform

49. Which transform has very good energy compaction for images?

COSINE Transform
HADAMARD Transform
SLANT Transform
HAAR Transform

50. The basic vectors of Slant matrix are

Uniformly ordred
sequensely ordered
Randomly ordred
not sequensely ordered

51. The basic vectors of HAAR matrix are

Uniformly ordred
sequensely ordered
Randomly ordred
not sequensely ordered

52. Which Transform is an optimal in the sense that it minimizes the mean square error between the
vectors X and their approximations X^?

KL Transform
HADAMARD Transform
SLANT Transform
HAAR Transform

53. Which Transform is very good energy compaction for highly correlated images?

KL Transform
HADAMARD Transform
SLANT Transform
HAAR Transform

54. Which Transform has excellent energy compaction for highly correlated data?

SLANT Transform
HADAMARD Transform
COSINE Transform
HAAR Transform

55. A measure of the smallest discernible detail in an image is

Intensity Resolution
Frequency Resolution
Spatial resolution
Spectral resolution

56. The negative of an image with gray levels in the range [0,L-1] is obtained by using the negative
transformation given as:

s=(L+1)-r
s=(L-1)-r
s=(L-1)+r
s=(L+1)+r

57. Which domain refers to image plane itself?

Laplace
Frequency
Spatial
Spectral

58. Which method is based on modifying the image by Fourier transform?

Image domain
Frequency domain
Spatial domain
Spectral domain

59. Which operation reduces an image of higher contrast than the original by darkening the levels
below m and brightening the levels above m in the image?

Contrast stretching
Grey level slicing
Bit plane slicing
Subjective Brightness

60. Which operation is used in enhancing masses of water in satellite imagery?

Contrast stretching
Grey level slicing
Bit plane slicing
Subjective Brightness

61. Which operation is used in enhancing flaws in x-ray images?

Contrast stretching
Grey level slicing
Bit plane slicing
Subjective Brightness

62. Which operation is used in highlighting the contribution made to total image appearance by
specific bits might be desired?

Contrast stretching
Grey level slicing
Bit plane slicing
Subjective Brightness

63. The histogram of a digital image with gray levels in the range [0,L-1] is h(rk)=

k
nk
n
n/k

64. An information about the degradation must be extracted from the observed image either explicitly
or implicitly is called as

Blind image restoration
Inverse Filtering
Least Mean square filtering
Singular value Decomposition

65. This PDF P(Z)= 2(z-a)e-(z—a)2/b/b for Z>=a belongs to which noise model?

Gaussian noise
Erlang noise
Rayleigh noise
Impulse Noise

66. This PDF P(Z)=e-(Z-µ)2/2σ2/√2πσ belongs to which noise model?

Gaussian noise
Gamma Noise
Rayleigh noise
Impulse Noise

67. This PDF P(Z)=ab zb-1 ae-az/(b-1) for Z>=0 belongs to which noise model?

Gaussian noise
Erlang noise
Uniform noise
Gamma Noise

68. This PDF P(Z)= ae-az

Z>=0 belongs to which noise model?

Gaussian noise
Exponential noise
Rayleigh noise
Gamma Noise

69. This PDF P(Z)=1/(b-a) if a<=Z<=b belongs to which noise model?

Gaussian noise
Erlang noise
Uniform noise
Gamma Noise

70. ------------ is the process of recovering the input of the system from its output?

Blind image restoration
Inverse Filtering
Least Mean square filtering
Singular value Decomposition

71. Wiener filtering is a method of restoring images in the

presence of blurr as well as noise
presence of noise only
abscence of blurr as well as noise
absence of blurr only

72. Which transform gives best energy packing efficiency for any given image?

SLANT Transform
HADAMARD Transform
SVD Transform
HAAR Transform

73. Which transform is useful in the design of filters finding least square?

SLANT Transform
HADAMARD Transform
KL Transform
SVD Transform

74. Hotteling Transform is also called as

KL Transform
HAAR Transform
SLANT Transform
SVD Transform

75. Which transform involves Principle of component analysis

SLANT Transform
HADAMARD Transform
KL Transform
SVD Transform

76. The basis of reduction process is removal of redundant data is called

image compression
image segmentation
image restoration
image enhancement

77. The pseudo inverse filter is defined as

H^(u,v)=1/(H(u,v)
H^(u,v)=1/(H(u,v)
H^(u,v)=(H(u,v)
H^(u,v)=(H(u,v)

78. This function represents which filter?

Contra harmonic mean filter
Geometric mean filter
Harmonic filters
Arithmetic mean filter

79. This function represents which filter?

Arithmetic mean filter
Geometric mean filter
Harmonic filters
Contra harmonic mean filter

80. This function represents which filter?

Arithmetic mean filter
Geometric mean filter
Contra harmonic mean filter
Harmonic filters

81. This function represents which filter?

Arithmetic mean filter
Geometric mean filter
Harmonic filters
Contra harmonic mean filter

82. The effect of salt and pepper noise can be eliminated using

Arithmetic mean filter
Geometric mean filter
Contra harmonic mean filter
Harmonic filters

83. Which filter has positive coefficient near the center and negative in the outer periphery.

Median filter
High pass spatial filter
Derivative filter
Low pass spatial filter

84. The first derivative at any point in an image is obtained by using

Laplacian at that point
the magnitude of the gradient at that point
the phase of the gradient at that point
Fourier transform at that point

85. The second derivative at any point in an image is obtained by using

Laplacian at that point
the magnitude of the gradient at that point
the phase of the gradient at that point
Fourier transform at that point

86. Compression Ratio =

original size - compressed size: 1
original size * compressed size: 1
original size + compressed size: 1
original size / compressed size: 1

87. Which is a technique used to reduce the size of a repeating string of characters?

Huffman coding
Runlength coding
Arithmetic coding
LZW coding

88. Run length coding is the example of

coding redundancy
compression redundancy
psycho visual redundancy
interpixel redundancy

89. ------------ transforms the input data into non-visual format.

Symbol encoder
Mapper
Quantizer
Symbol decoder

90. Which of this step is omitted if the system is error free.

Symbol encoder
Mapper
Quantizer
Symbol decoder

91. ----------- reduces the coding redundancy.

Symbol encoder
Mapper
Quantizer
Symbol decoder

92. ---------- reduces the interpixel redundancy.

Symbol encoder
Mapper
Quantizer
Symbol decoder

93. -------------- reduces the psycho visual redundancy of the input images.

Symbol encoder
Mapper
Quantizer
Symbol decoder

94. Hamming code is the example for

Symbol encoder
Mapper
Quantizer
Channel encoder

95. Variable Length Coding reduces

coding redundancy
compression redundancy
psycho visual redundancy
interpixel redundancy

96. A code word that is not a prefix of any other code word is called

Huffman code
Block code
Instantaneous code
Arithmetic code

97. One to one corresponds between source symbols and code word doesn’t exist in

Huffman code
Block code
LZW code
Arithmetic code

98. JPEG stands for

Joint Pixel Expert Group
Joint Photographic Expert Group
Joint Photographic Expand Group
Joint Picture Expert Group

99. Data Redundancy Rd =

1-Cr
1/Cr
1-1/Cr
1+1/Cr

Calculate the data redundancy if N1 = 2 , n2 =1

0.5
1
0
-1


Download this one mark with Answers

PREPARED BY

___
Er. M. ARUN M.E. MIEEE, MISTE

LECTURER ECE

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