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The Structural Similarity Index (SSIM) is really a perceptual metric that quantifies the image quality degradation this is certainly due to processing such as for instance information compression or by losings in information transmission. This metric is simply a complete reference that needs 2 pictures through the exact same shot, what this means is 2 graphically identical pictures towards the eye that is human. The 2nd image generally speaking is compressed or has a different sort of quality, which can be the aim of this index. SSIM is generally found in the movie industry, but has too an application that is strong photography. SIM really steps the difference that is perceptual two comparable pictures. It cannot judge which associated with two is way better: that must definitely be inferred from once you understand which will be the initial one and which was subjected to extra processing such as for instance compression or filters.
In this essay, we will show you just how to compute this index between 2 pictures utilizing Python.
Demands
To adhere to this guide you will require:
- Python 3
- PIP 3
That being said, let’s get going !
1. Install Python dependencies
Before applying the logic, you need to install some important tools that will undoubtedly be utilized by the logic. This tools may be set up through PIP because of the after demand:
These tools are:
- scikitimage: scikit-image is an accumulation algorithms for image processing.
- opencv: OpenCV is really a library that is highly optimized give attention to real-time applications.
- imutils: a number of convenience functions to create basic image processing functions such as for example interpretation, rotation, resizing, skeletonization, showing Matplotlib pictures, sorting contours, detecting sides, and more easier with OpenCV and both Python 2.7 and Python 3.
This guide will focus on any platform where Python works (Ubuntu/Windows/Mac). Continue reading “Simple tips to calculate the Structural Similarity Index (SSIM) between two images with Python”