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The Structural Similarity Index (SSIM) is a perceptual metric that quantifies the image quality degradation that is due to processing such as for instance information compression or by losings in information transmission. This metric is actually the full reference that will require 2 pictures through the exact same shot, this implies 2 graphically identical pictures to your eye. The 2nd image generally speaking is compressed or has a different sort of quality, that will be the aim of this index. SSIM is normally utilized in the video clip industry, but has aswell an application that is strong photography. SIM really steps the difference that is perceptual two comparable pictures. It cannot judge which regarding the two is much better: that needs to be inferred from once you understand which will be the initial one and that has been subjected to additional processing such as for instance compression or filters.
In this essay, we will explain to you how exactly to calculate accurately this index between 2 pictures utilizing Python.
To adhere to this tutorial you shall need:
- Python 3
- PIP 3
With that said, allow’s begin !
1. Install Python dependencies
Before applying the logic, you need to install some tools that are essential is going to be utilized by the logic. This tools are installed through PIP aided by the after demand:
These tools are:
- scikitimage: scikit-image is an accumulation of algorithms for image processing.
- opencv: OpenCV is really a very optimized collection with concentrate on real-time applications.
- imutils: a few convenience functions in order to make image that is basic functions such as for example translation, rotation, resizing, skeletonization, displaying Matplotlib pictures, sorting contours, detecting edges, and more easier with OpenCV and both Python 2.7 and Python 3.
This guide shall work with any platform where Python works (Ubuntu/Windows/Mac). Continue reading “How exactly to calculate the Structural Similarity Index (SSIM) between two images with Python”