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(Bio)Image Analysis with Python: Everything You Need to Know about Histograms
Computer Vision   Data Science   Latest   Machine Learning

(Bio)Image Analysis with Python: Everything You Need to Know about Histograms

Last Updated on December 11, 2023 by Editorial Team

Author(s): MicroBioscopicData

Originally published on Towards AI.

Learn Computer Vision Concepts Using Python

Welcome to our series (Bio)Image Analysis with Python: Everything You Need to Know. In this tutorial, we dive into Histograms, an important tool, and discover how it plays a crucial role in the world of computer vision and Bioimage analysis. What sets this tutorial apart is our practical approach: we’ll use Python to illustrate the usefulness of histograms in Microscopy.

As we have already discussed in our previous tutorial, images are composed of picture elements (pixels), and as far as the computer is concerned, each pixel is just a number. When the image data is displayed, the values of pixels are usually converted into squares; the squares are nothing more than a helpful visualization that enables us to gain a fast impression of the image content [1].

Since images are essentially data, we can employ histograms to gain a better understanding of them.

1 Creating a Histogram2 Histograms and Image Acquisition3 Comparing Images and Histograms4 Appearances Can Be Deceptive5 Histograms as Tools6 Conclusion7 References:

What is a histogram?

A histogram is a visual representation of the distribution of pixel intensities in an image. It provides a visual summary of the total distribution in an image, showing how many pixels have… Read the full blog for free on Medium.

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