Its already one year over for the 2010 batches. Usually Software companies won't recruit freshers when they have more than one year gap. But with the recession of the last few years IT companies are recruiting freshers even they have more than one year gap. Wipro has called the 2010 passed out batches to attend the interview. They are recruiting 2010 BE/B.Tech passed outs. Even they are calling for the 2009 passed outs. I hope this is the last chance for the 2009 and 2010 passed outs. You can apply directly from the Wipro's website. Click Here to apply to Wipro. This link will redirect you to the Wipro's website. Last day to apply for this job is 30th May 2011. Apply for the job. They will call you or mail you for the interview. All the best for your interview.
Saturday, May 28, 2011
Chetanas has created a new website for Java Programers
Day by day JAVA programmers are increasing. Most of the applications are done through Java coding. We can do any kind of applications with JAVA. All the companies are hiring JAVA professionals. Every company are in need of JAVA professionals. Its easy to get a job if you know JAVA. But the pay will be vary from company to company. Chetanas forun is one of the best online job portal as they are doing wonderful job for the freshers as well as the experienced professionals. The percentage of fake jobs was less when compared to other job portals. We can assure the company posted in chetanas forum was a good company. Now Chetanas forum has a new portal for JAVA professionals. We can search JAVA programming vacancies in this portal.Click Here to visit the portal for JAVA vacancies. The portal name is http://javaken.com
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
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
Monday, May 9, 2011
Lock and Unlock Folders Using Text files
Windows needs special software's to lock and unlock the files. But windows itself providing the feature to lock and unlock the files. Here i am going to explain about the options to lock and unlock the files using the notepad.
First create a folder with any name (ex. bensh)
Now open a notepad and type the following inthe notepad
ren bensh bensh.{21EC2020-3AEA-1069-A2DD-08002B30309D}
now save the file with the name lock.bat.
Now open a new notepad and type the following in the notepad.
ren bensh.{21EC2020-3AEA-1069-A2DD-08002B30309D}bensh
now Save the file with the name key.bat.
Now Double click on the lock.bat file.
The folder will be locked.
To open the folder double click on the key.bat file.
Note that the lock.dat and the key.dat files should be in the same folder where the bensh folder was there.
This lock technique will not work in the Windows 7 OS.
First create a folder with any name (ex. bensh)
Now open a notepad and type the following inthe notepad
ren bensh bensh.{21EC2020-3AEA-1069-A2DD-08002B30309D}
now save the file with the name lock.bat.
Now open a new notepad and type the following in the notepad.
ren bensh.{21EC2020-3AEA-1069-A2DD-08002B30309D}bensh
now Save the file with the name key.bat.
Now Double click on the lock.bat file.
The folder will be locked.
To open the folder double click on the key.bat file.
Note that the lock.dat and the key.dat files should be in the same folder where the bensh folder was there.
This lock technique will not work in the Windows 7 OS.
Sunday, May 8, 2011
Clean Up your PC and Improve the performance
Most of the people are using computers. All the offices and colleges have the computers for the business as well as for educational purpose. The computer’s plays an important role in the technology world. Every people are in need of computers in their daily life. Many applications have come to improve the business.
Every one use computer. But not everyone use the computer efficiently. Most of the computers will slow down the performance after some months. This is because of the unwanted memory in the hard disk. Windows provides some tools to improve the performance of the computer. These tools are Disk Cleanup, Disk Defragmenter, and Check Disk. We will see about how to do Disk Cleanup and make your computer works faster. Better do automatic schedule for Disk cleanup instead of doing it manually.
Follow the below steps to perform the Disk Cleanup:
Windows 7:
- Open Task Scheduler: Click the Start button, click Control Panel, click Administrative Tools, and then double-click Task Scheduler. If you're prompted for an administrator password or confirmation, type the password or provide confirmation.
- Click the Action menu, and then click Create Basic Task. This opens the Create Basic Task Wizard.
- Type a name for the task and an optional description, and then click Next.
- To select a schedule based on the calendar, click Daily, Weekly, Monthly, or One time, and then click Next.
- Specify the schedule you want to use, and then click Next.
- Click Start a program, and then click Next.
- Click Browse, and, in the File name box, type cleanmgr.exe, click Open, and then click Next.
- Click Finish.
- Open Task Scheduler: Click the Start button, click Administrative Tools, and then click Task Scheduler. If you are prompted for an administrator password or confirmation, type the password or provide confirmation.
- Click the Action menu, and then click Create Basic Task.
- Type a name for the task and an optional description, and then click Next.
- To select a schedule based on the calendar, click Daily, Weekly, Monthly, or One time, and then click Next.
- Specify the schedule you want to use, and then click Next.
- Click Start a program, and then click Next.
- Click Browse, and, in the File name box, type cleanmgr.exe, click Open, and then click Next.
- Click Finish.
- Click Start, and then click Control Panel.
- Click Performance and Maintenance.
- Under or pick a Control Panel icon, click Scheduled Tasks.
- In the Scheduled Tasks window, double-click Add Scheduled Task.
- In the Scheduled Task Wizard, click Next.
- Scroll down to Disk Cleanup in the list of Applications, click it (to highlight it), and then click Next.
- Under Perform this task, click Weekly, and then click Next.
- Set the time and day of the week you would like to run Disk Cleanup. For best results, choose a time when you're typically at your computer so you can provide any required input. Click Next.
- Type your password in both the Enter the password and Confirm password boxes, and then click Next.
- Click Finish.
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