Q
Which of the following techniques is commonly used to adjust image brightness and contrast?

Answer & Solution

Answer: Option B
Solution:
Histogram equalization is commonly used to adjust image brightness and contrast.
Related Questions on Average

Which effect can be achieved by setting all RGB channels of a pixel to the same value?

A). Sepia tone effect

B). Blur effect

C). Grayscale conversion

D). Color inversion effect

What does the Gaussian blur effect primarily enhance in an image?

A). Edges and details

B). Image brightness

C). Image color saturation

D). Image noise

Which effect can be achieved by increasing the contrast between adjacent pixels?

A). Sharpening effect

B). Sepia tone effect

C). Color inversion effect

D). Blur effect

What is the purpose of applying color gradients in image editing?

A). To add texture

B). To blend colors and create transitions

C). To reduce image size

D). To add noise to images

Which method is commonly used to manipulate individual pixels in an image?

A). alterPixel()

B). setPixel()

C). adjustPixel()

D). modifyPixel()

How does adjusting the hue and saturation of an image affect its appearance?

A). It changes image size

B). It alters image colors

C). It reduces image noise

D). It adds transparency to images

How does the color depth of an image affect the quality of image filters and effects?

A). Higher color depth results in better quality

B). Lower color depth results in better quality

C). Color depth has no impact on quality

D). Color depth affects image size only

How can a sepia tone effect be achieved using pixel manipulation techniques?

A). By increasing color saturation

B). By adjusting RGB channel values

C). By decreasing image brightness

D). By applying a blur effect

Which statement best describes the sharpening effect in image editing?

A). It increases image size

B). It reduces image contrast

C). It enhances image edges

D). It adds noise to images

Which technique is commonly used to remove image noise and artifacts?

A). Sharpening effect

B). Histogram equalization

C). Gaussian blur effect

D). Color inversion effect