Question 1

The principle objective of Sharpening, to highlight transitions is ___________________.
A)pixel density
B)composure
C)intensity
D)brightness

Accepted Answer

Sharpening enhances the contrast at edges within an image, making transitions between different regions more pronounced, which is related to intensity rather than pixel density, composure, or brightness.

Question 2

How can Sharpening be achieved?
A)pixel averaging
B)slicing
C)correlation
D)none of the mentioned

Accepted Answer

Sharpening is achieved through methods like edge detection and enhancement, not through pixel averaging, slicing, or correlation. These techniques mentioned do not inherently sharpen an image.

Question 3

What does Image Differentiation enhance?
A)edges
B)pixel density
C)contours
D)none of the mentioned

Accepted Answer

Image Differentiation enhances edges by highlighting the changes in intensity between adjacent pixels, which is useful for edge detection in image processing.

Question 4

What does Image Differentiation de-emphasize?
A)pixel density
B)contours
C)areas with slowly varying intensities
D)none of the mentioned

Accepted Answer

Image differentiation emphasizes edges and contours where the intensity changes rapidly and de-emphasizes areas with slowly varying intensities, making it useful for edge detection and other applications that require highlighting changes in intensity.

Question 5

The requirements of the First Derivative of a digital function:
A)must be zero in areas of constant intensity
B)must be non-zero at the onset of an intensity step
C)must be non-zero along ramps
D)all of the mentioned

Accepted Answer

The first derivative of a digital function indeed must be zero in areas of constant intensity, non-zero at the onset of an intensity step, and non-zero along ramps, as these conditions describe the changes in intensity that the derivative is meant to capture.

Question 6

What is the Second Derivative of Image Sharpening called?
A)gaussian
B)laplacian
C)canny
D)none of the mentioned

Accepted Answer

The second derivative of image sharpening is called Laplacian, which is used to emphasize regions of rapid intensity change and is therefore often used for edge detection.

Question 7

The ability that rotating the image and applying the filter gives the same result, as applying the filter to the image first, and then rotating it, is called ______________________.
A)isotropic filtering
B)laplacian
C)rotation invariant
D)none of the mentioned

Accepted Answer

Rotation invariance is the property that describes the ability to obtain the same result by either rotating the image and then applying a filter, or applying the filter first and then rotating the image. This means the filter's effect on the image does not depend on the image's orientation.

Question 8

For a function f(x,y), the gradient of 'f' at coordinates (x,y) is defined as a ____________________.
A)3-d row vector
B)3-d column vector
C)2-d row vector
D)2-d column vector

Accepted Answer

The gradient of a function f(x,y) at any point (x,y) is defined as a 2-dimensional column vector, which consists of the partial derivatives of the function with respect to x and y.

Question 9

Where do you find frequent use of Gradient?
A)industrial inspection
B)mri imaging
C)pet scan
D)none of the mentioned

Accepted Answer

The answer of Where do you find frequent use of...

Question 10

Which of the following occurs in Unsharp Masking?
A)blurring original image
B)adding a mask to original image
C)subtracting blurred image from original
D)all of the mentioned

Accepted Answer

Unsharp Masking involves blurring the original image, subtracting the blurred image from the original to create a mask, and then adding this mask back to the original image to enhance its sharpness, thus involving all the mentioned steps.

Question 11

Which of the following make an image difficult to enhance?
A)narrow range of intensity levels
B)dynamic range of intensity levels
C)high noise
D)all of the mentioned

Accepted Answer

All the mentioned factors make an image difficult to enhance. A narrow range of intensity levels limits contrast, a dynamic range of intensity levels can make it hard to optimize for all parts of an image, and high noise can obscure details and make it difficult to improve image quality without introducing artifacts.

Question 12

Which of the following is a second-order derivative operator?
A)histogram
B)laplacian
C)gaussian
D)none of the mentioned

Accepted Answer

The Laplacian is a second-order derivative operator used in image processing for edge detection, among other applications. It measures the rate at which the first derivatives change, providing information about the curvature of the image's intensity landscape.

Question 13

Response of the gradient to noise and fine detail is _____________ the Laplacian's.
A)equal to
B)lower than
C)greater than
D)has no relation with

Accepted Answer

The response of the gradient to noise and fine detail is lower than the Laplacian's because the gradient measures the rate of change in brightness, which can be less sensitive to fine details and noise compared to the Laplacian, which measures the second derivative and is more sensitive to rapid changes in intensity, including noise and fine details.

Question 14

Dark characteristics in an image are better solved using ____________________.
A)laplacian transform
B)gaussian transform
C)histogram specification
D)power-law transformation

Accepted Answer

Dark characteristics in an image are better solved using power-law transformation. This technique enhances the visibility of details in dark regions by adjusting the gamma value, effectively brightening the image without losing details.

Question 15

What is the smallest possible value of a gradient image?
A)e
B)1
C)0
D)-e

Accepted Answer

The smallest possible value of a gradient image is 0, indicating no change in intensity between neighboring pixels.

Question 16

Which of the following fails to work on dark intensity distributions?
A)laplacian transform
B)gaussian transform
C)histogram equalization
D)power-law transformation

Accepted Answer

Histogram equalization may not work effectively on images with dark intensity distributions because it aims to spread out the most frequent intensity values, but if an image is already dark, this method might not significantly improve the contrast or visibility of the image.

Question 17

_________________________ is used to detect diseases such as bone infection and tumors.
A)mri scan
B)pet scan
C)nuclear whole body scan
D)x-ray

Accepted Answer

A nuclear whole body scan is used to detect diseases such as bone infections and tumors by using radioactive substances to visualize the structure and function of organs and tissues.

Question 18

How do you bring out more of the skeletal detail from a Nuclear Whole Body Bone Scan?
A)sharpening
B)enhancing
C)transformation
D)none of the mentioned

Accepted Answer

Sharpening is a technique used in image processing to enhance the visibility of edges and fine details in images, which can help in bringing out more of the skeletal detail in a Nuclear Whole Body Bone Scan.

Question 19

Final step of enhancement lies in ________________ of the sharpened image.
A)increase range of contrast
B)increase range of brightness
C)increase dynamic range
D)none of the mentioned

Accepted Answer

The final step of enhancement in the context of sharpening an image often involves increasing the dynamic range. This helps in making the details more pronounced and improving the overall visual quality of the image.

Question 20

An alternate approach to median filtering is ______________
A)use a mask
B)gaussian filter
C)sharpening
D)laplacian filter

Accepted Answer

The answer of An alternate approach to median filtering is...

Quiz 5: Image Enhancement Techniques and Their Applications

The principle objective of Sharpening, to highlight transitions is ___________________.

How can Sharpening be achieved?

What does Image Differentiation enhance?

What does Image Differentiation de-emphasize?

The requirements of the First Derivative of a digital function:

What is the Second Derivative of Image Sharpening called?

The ability that rotating the image and applying the filter gives the same result, as applying the filter to the image first, and then rotating it, is called ______________________.

For a function f(x,y) , the gradient of 'f' at coordinates (x,y) is defined as a ____________________.

Where do you find frequent use of Gradient?

Which of the following occurs in Unsharp Masking?

Which of the following make an image difficult to enhance?

Which of the following is a second-order derivative operator?

Response of the gradient to noise and fine detail is _____________ the Laplacian's.

Dark characteristics in an image are better solved using ____________________.

What is the smallest possible value of a gradient image?

Which of the following fails to work on dark intensity distributions?

_________________________ is used to detect diseases such as bone infection and tumors.

How do you bring out more of the skeletal detail from a Nuclear Whole Body Bone Scan?

Final step of enhancement lies in ________________ of the sharpened image.

An alternate approach to median filtering is ______________