Image Enhancement

Author(s): Akula Hemanth Kumar

Originally published on Towards AI.

Making computer vision easy with Monk, low code Deep Learning tool and a unified wrapper for Computer Vision.

Table of contents

1. Image Enhancement
2. Pillow special functions
3. OpenCV CLAHE

Image Enhancement

Need for Enhancement

• Improve the interpretability or perception of information.
• Provide better input for other automated image processing techniques.

Image enhancement techniques can be divided into two broad categories

• Spatial domain methods, which operate directly on pixels.
• Frequency domain methods, which operate on the Fourier transform of an image.

Pillow special functions

Contour detection

Detail edge enhancement

Edge Detection

OpenCV CLAHE

Contrast limited adaptive histogram equalization

You can find the complete jupyter notebook on Github.

If you have any questions, you can reach Abhishek and Akash. Feel free to reach out to them.

I am extremely passionate about computer vision and deep learning in general. I am an open-source contributor to Monk Libraries.

You can also see my other writings at:

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI