Top Python Libraries for Image Processing

Python provides a vast collection of libraries that provide a wide range of tools and functionalities for manipulating, analyzing, and enhancing images. Whether someone is a developer working on image applications, a researcher, or a machine learning engineer there is a Python library for image processing that fulfills their requirement. In this article, we will learn about top Python libraries used for image processing.

What is Image Processing?

Image processing is the process of analysis, manipulation, and interpretation of images using computational power. Various algorithms and methods are used to transform, enhance, or extract information from images. One of the common examples is the face lock used in computers and mobile phones. The key objectives of image processing include:

1. Image Enhancement
2. Image Restoration
3. Image Compression
4. Image Segmentation
5. Object Recognition
6. Image Registration
7. Feature Extraction
8. Geometric Transformation
9. Color Image Processing
10. Pattern Recognition

Top Python Libraries

1. OpenCV

OpenCV is a open-source library for computer vision, machine learning, and image processing. Numerous programming languages, including Python, C++, Java, and others, are supported by OpenCV. It can recognize faces, objects, and even human handwriting by processing photos and movies.

pip install opencv-python

Grey Scaling using OpenCV

You can download the image from here.

Output:

👁 OpenCV

2. SciPy

A Python package called Scipy is helpful for resolving a variety of mathematical problems and procedures. It is built upon the NumPy library, which provides further flexibility in locating scientific mathematical formulas, including LU Decomposition, polynomial equations, matrix rank, and inverse.

python -m pip install scipy

Here are some key aspects of SciPy in terms of image processing:

1. Image Filters and Operations
2. Image Morphology
3. Image Measurements
4. Interpolation and Geometric Transformations
5. Integration with NumPy and Matplotlib

Blurring the Image using SciPy and Matplotlib

We're using SciPy's ndimage.gaussian_filter function to apply Gaussian blur to the input image.

Output:

👁 SciPy

3. ImageIO

ImageIO is a Python library developed with the purpose of reading and writing images in various formats. It simplifies the process of working with images by providing a unified interface for different file formats.

pip install imageio

Here are some key features of ImageIO library in Python:

1. Image Input and Output
2. Working with Video Files
3. Animated Image Support
4. Integration with NumPy
5. Flexible and Extensible

Reading Image using ImageIO

Output:

👁 image io

4. Scikit-Image

Scikit-Image is a Python module for image processing that utilizes NumPy arrays, a set of image processing methods. It provides a collection of algorithms for image processing, computer vision, and computer graphics.

We can install Scikit-Image library in Python by executing below command in the terminal.

pip install scikit-image

Here are some key features of Scikit-image library in Python:

1. Rich Collection of Algorithms
2. Easy Integration with NumPy
3. Image Segmentation
4. Feature Extraction
5. Image Restoration
6. Visualization Tools

Edge Detection using Scikit-image

Output:

👁 scikit-image

5. Python Image Library (PIL/Pillow)

Python Imaging Library (an extension of PIL) is the de facto image processing package for the Python language. It includes simple image processing capabilities to help with image creation, editing, and archiving. It is compatible with a wide range of image file types, such as TIFF, JPEG, PNG, and BMP.

We can install PIL/Pillow library in Python by executing below command in the terminal.

pip install pillow

Here are some key features of PIL/Pillow library in Python:

1. Image Opening and Saving
2. Image Manipulation
3. Image Filtering and Enhancements
4. Image Drawing
5. Image Conversion and Formats
6. Integration with NumPy
7. Handling Animated Images

Cropping Image using Pillow

Output:

👁 PIL

6. Mahotas

Mahotas is a Python library used for computer vision, image processing, and manipulation. Mahotas is an array-based algorithm suite that has more than 100 functions for computer vision and image processing, and it is still expanding.

To install Mahotas library in Python execute the below command in the terminal.

pip install mahotas

Here are some key features of the Mahotas library:

1. Fast Image Processing
2. Filtering and Convolution
3. Morphological Operations
4. Feature Extraction
5. Image Segmentation
6. Histograms and Thresholding
7. Distance Transform
8. Integration with NumPy

Converting the Image in Different Tone using Mahotas

Output:

👁 manhatos

7. Matplotlib

Matplotlib is a Python visualization package for two-dimensional array charts. Matplotlib is based on NumPy array and a multi-platform data visualization package intended to be used with the larger SciPy stack. Many plot types, including line, bar, scatter, histogram, and more, are available in Matplotlib.

We can install Matplotlib by executing below command.

pip install matplotlib

Here are some key features of Matplotlib in the context of image processing:

1. Image Display
2. Subplots and Multi-image Display
3. Histograms
4. Visualizing Filters
5. Custom Annotations and Overlays
6. Color Maps and Colorbars
7. Saving Figures

8. SimpleCV

SimpleCV is an open-source framework used for computer vision tasks. It has simplified computer vision, as its name would imply. SimpleCV offers easy-to-use practices for completing common computer vision tasks, eliminating the complexity associated with OpenCV.

We can install SimpleCV by using below command in the terminal.

pip install SimpleCV

Here are some key features of SimpleCV:

1. Easy Image Processing
2. Computer Vision Utilities
3. Camera Support
4. Integration with NumPy
5. Feature Detection and Matching
6. Interactive Shell
7. Extensibility

9. SimpleITK

SimpleITK stands for simple Insight Segmentation and Registration Toolkit. It is a powerful open source library implemented in C++ and used for medical image analysis. To install this library, execute below command in the terminal.

pip install SimpleITK

Here are some key features of SimpleCV:

1. Simplified Interface
2. Image Loading and Manipulation
3. Image Registration
4. Image Segmentation
5. Image Filtering
6. Image Visualization
7. Cross-Platform Compatibility

10. Pgmagick

Pgmagick is a Python binding for GraphicsMagick that offers several image manipulation functions, including text drawing, gradient picture creation, sharpening, resizing, and rotating.

To install this library execute below command in the teminal.

pip install pgmagick

Here are some key features of Pgmagick:

1. Image Manipulation
2. Image Filtering and Effects
3. Drawing and Annotation
4. Image Analysis
5. Batch Processing
6. High Performance
7. Cross-Platform Compatibility