# Spatial and Gray-Level Resolution MCQ [Free PDF] – Objective Question Answer for Spatial and Gray-Level Resolution Quiz

1. The principal factor to determine the spatial resolution of an image is _______

A. Quantization
B. Sampling
C. Contrast
D. Dynamic range

The spatial resolution of an image is principally determined by Sampling.

2. What causes the effect, imperceptible set of the very fine ridge-like structures in areas of smooth gray levels?

A. Caused by the use of an insufficient number of gray levels in smooth areas of a digital image
B. Caused by the use of a huge number of gray levels in smooth areas of a digital image
C. All of the mentioned
D. None of the mentioned

The set of the very fine ridge-like structures in the area of smooth gray levels generally is quite visible in images displayed using 16 or less uniformly spaced gray levels.

3. What is the name of the effect caused by the use of an insufficient number of gray levels in smooth areas of a digital image?

A. Dynamic range
B. Ridging
C. Graininess
D. False contouring

The effect caused due to an insufficient number of gray levels in smooth areas of a digital image is called false contouring, so-called because the ridges resemble topographic contours on a map.

4. Using a rough rule of thumb, and assuming powers of 2 for convenience, what image size is about the smallest images that can be expected to be reasonably free of objectionable sampling checkerboards and false contouring?

A. 512*512pixels and 16 gray levels
B. 256*256pixels and 64 gray levels
C. 64*64pixels and 16 gray levels
D. 32*32pixels and 32 gray levels

An image of 128*128pixels shows a pronounced checkerboard pattern, while for a 256*256pixels image a minimum gray level of 64 is required to remove false contouring.
Also, the effect is quite visible in images displayed using 16 or less uniformly spaced gray levels.

5. What does a shift up and right in the curves of isopreference curve simply means? Verify-in terms of N (number of pixels) and k (L=2k, L is the gray level) values.

A. Smaller values for N and k, implies a better picture quality
B. Larger values for N and k, imply low picture quality
C. Larger values for N and k, imply better picture quality
D. Smaller values for N and k, imply low picture quality

Points lying on an isopreference curve correspond to images of equal subjective quality. It was found that the isopreference curves tended to shift right and upward with the details of the image. So, a shift up and right in the curves simply means larger values for N and k, implying better picture quality.

6. How do the curves behave to the detail in the image in isopreference curve?

A. Curves tend to become more vertical as the detail in the image decreases
B. Curves tend to become less vertical as the detail in the image increases
C. Curves tend to become less vertical as the detail in the image decreases
D. Curves tend to become more vertical as the detail in the image increases

The curves in isopreference curve tend to become more vertical as the detail in the image increases.
The right side graph shows the same, the curve for a crowd is nearly vertical.

7. For an image with a large amount of detail, if the value of N (number of pixels) is fixed then what is the gray level dependency in the perceived quality of this type of image?

A. independent of the number of gray levels used
B. Nearly independent of the number of gray levels used
C. Highly dependent on the number of gray levels used
D. None of the mentioned

For images with high details of the image, only a few gray levels may be needed.

8. What is a band-limited function?
A. A function of limited duration whose highest frequency is finite
B. A function of limited duration whose highest frequency is infinite
C. All of the mentioned
D. None of the mentioned

Functions whose area under the curve is finite can be represented in terms of sines and cosines of various frequencies. The highest frequency is determined by the sine/cosine component is the highest “frequency content” of the function. If this highest frequency is finite and the function is of unlimited duration, then, these functions are called band-limited functions.

9. For a band-limited function, which Theorem says that “if the function is sampled at a rate equal to or greater than twice its highest frequency, the original function can be recovered from its samples”?

A. Band-limitation theorem
B. Aliasing frequency theorem
C. Shannon sampling theorem
D. None of the mentioned

For a band-limited function, the Shannon sampling theorem says that “if the function is sampled at a rate equal to or greater than twice its highest frequency, the original function can be recovered from its samples”.

10. What is the name of the phenomenon that corrupts the sampled image, and how does it happen?

A. Shannon sampling, if the band-limited functions are undersampled
B. Shannon sampling, if the band-limited functions are oversampled
C. Aliasing if the band-limited functions are undersampled
D. Aliasing, if the band-limited functions are oversampled

If the band-limited functions are undersampled, then a phenomenon called aliasing corrupts the sampled image.

11. How aliasing does corrupt the sampled image?

A. By introducing additional frequency components to the sampled function
B. By removing some frequency components from the sampled function
C. All of the mentioned
D. None of the mentioned

Aliasing corrupts the sampled image by introducing additional frequency components into the sampled function. These added components are called aliased frequencies.

12. How can one reduce the aliasing effect on an image?

A. By reducing the high-frequency components of the image by blurring the image
B. By increasing the high-frequency components of the image by blurring the image
C. By reducing the high-frequency components of the image by clarifying the image
D. By increasing the high-frequency components of the image by clarifying the image

Aliasing corrupts the sampled image by introducing additional frequency components to the sampled function. So, the principal approach for reducing the aliasing effects on an image is to reduce its high-frequency components by blurring the image before sampling.

13. In terms of Sampling and Quantization, Zooming and Shrinking may be viewed as ___________

A. Oversampling for both
B. Oversampling and Undersampling respectively
C. Undersampling and Oversampling respectively
D. Undersampling for both

Oversampling increases the number of samples in the image, i.e. Zooming. Undersampling decreases the number of samples in the image, i.e. Shrinking.

14. The two steps: one is the creation of new pixel locations, and the other is the assignment of gray levels to those new locations are involved in ____________

A. Shrinking
B. Zooming
C. All of the mentioned
D. None of the mentioned

Suppose that we have an image of size500*500pixels and we want to enlarge it 1.5 times to 750*750 pixels.

Creation of new Pixels: One of the easiest ways to visualize zooming is laying an imaginary 750*750 grid over the original image and so there would be less spacing by one pixel in the grid because we are fitting it over a smaller image.

Assignment of gray levels to new locations: To perform a gray-level assignment for any point in the overlay, we assign its gray level to the new pixel in the grid its closest pixel in the original image.

When the above steps are done with all points in the overlay grid, we expand it to the originally specified size to obtain the zoomed image.

15. While Zooming, In order to perform a gray-level assignment for any point in the overlay, we assign its gray level to the new pixel in the grid its closest pixel in the original image. What’s this method of gray-level assignment called?

A. Neighbor Duplication
B. Duplication
C. Nearest neighbor Interpolation
D. None of the mentioned

Because we look for the closest pixel in the original image and assign its gray level to the new pixel in the grid.

16. A special case of nearest-neighbor Interpolation that just duplicates the pixels the number of times to achieve the desired size, is known as ___________

A. Bilinear Interpolation
B. Contouring
C. Ridging
D. Pixel Replication

A special case of nearest-neighbor interpolation is Pixel replication and is applicable when we want to increase the size of an image an integer number of times.

For example, doubling the size of an image is achieved by duplicating each column, and hence image size gets doubled in the horizontal direction. Then, we duplicate each row of the enlarged image to double the size in the vertical direction. Similarly, enlarging the image by an integer number of times (triple, quadruple, and so on) is possible.

17. Nearest neighbor Interpolation has an undesirable feature, that is _________

A. Aliasing effect
B. False contouring effect
C. Ridging effect
D. Checkerboard effect

At greater magnification nearest neighbor Interpolation has the undesirable feature of producing a checkerboard effect.

18. What does the bilinear Interpolation do for a gray-level assignment?

A. Assign gray level to the new pixel using its right neighbor
B. Assign a gray level to the new pixel using its left neighbor
C. Assign gray level to the new pixel using its four nearest neighbors
D. Assign a gray level to the new pixel using its eight nearest neighbors

Bilinear interpolation uses the four nearest neighbors of the new pixel. Let (x’, y’) be the coordinates of a point in the zoomed image, and the gray level assigned to the point is v(x, y’).

For bilinear interpolation, the assigned gray level is given by
v(x’, y’) = ax’ + by’ + cx’y’ + d
Here, a, b, c, and d are determined from the four equations in four unknowns that can be written using the four nearest neighbors of point (x’, y’).

19. Row-column deletion method of Image Shrinking is an equivalent process to which method of Zooming?

A. Bilinear Interpolation
B. Contouring
C. Pixel Replication
D. There is no such equivalent process

Row-column deletion method is used to shrink an image by one-half, one-fourth, and so on.
In the case of one-half, we delete every other row and column.

20. Image Shrinking has an undesirable feature, that is ____________

A. Aliasing effect
B. False contouring effect
C. Ridging effect
D. Checkerboard effect