Histogram computation in Computer Vision - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a histogram in the context of computer vision?

A histogram is a graphical representation that shows the distribution of pixel intensities or colors in an image. It counts how many pixels have each intensity value.

beginner

Why do we compute histograms of images?

Histograms help us understand the brightness and contrast of an image, detect patterns, and are used in tasks like image enhancement, segmentation, and object recognition.

beginner

How is a grayscale image histogram computed?

For each pixel, find its intensity value (0-255). Count how many pixels have each intensity. The counts form the histogram bins.

intermediate

What does histogram equalization do?

Histogram equalization redistributes pixel intensities to improve image contrast by spreading out the most frequent intensity values.

intermediate

How can histograms be used in color images?

Histograms can be computed separately for each color channel (Red, Green, Blue) to analyze color distribution and perform color-based image processing.

What does each bin in an image histogram represent?

A Number of pixels with a specific intensity

B Coordinates of pixels

C Color of the image

D Size of the image

Each bin counts how many pixels have a particular intensity value.

Which of the following is a use of histogram equalization?

A Improving image contrast

B Reducing image size

C Changing image format

D Removing noise

Histogram equalization improves contrast by spreading out intensity values.

In a grayscale image, what is the typical range of pixel intensity values?

A 0 to 1

B 0 to 1000

C 0 to 255

D -128 to 127

Grayscale pixel intensities usually range from 0 (black) to 255 (white).

How are histograms computed for color images?

A By combining all colors into one histogram

B By ignoring color and using grayscale

C Only for the red channel

D Separately for each color channel

Histograms are computed separately for Red, Green, and Blue channels.

What can a histogram tell us about an image?

A The image's file size

B The distribution of pixel intensities

C The camera used to take the image

D The image's resolution

A histogram shows how pixel intensities are distributed in the image.

Explain how to compute a histogram for a grayscale image and why it is useful.

Think about counting pixels for each shade of gray.

Describe how histogram equalization improves an image and when you might use it.

Consider how changing pixel brightness distribution affects image clarity.