SSIM.JS

Get a 0 to 1 score on how similar two images are

The closer SSIM is to 1 the higher the similarity. It correlates better with subjective ratings than other measures like PSNR and MSE. For instance:

Original, MSE = 0, SSIM = 1	MSE = 144, SSIM = 0.988	MSE = 144, SSIM = 0.913
MSE = 144, SSIM = 0.840	MSE = 144, SSIM = 0.694	MSE = 142, SSIM = 0.662

Table extracted from http://www.cns.nyu.edu/~lcv/ssim/

🖥 Install

npm install ssim.js

This will install the node, web and CLI versions.

Install it globally (npm install -g) to make ssim available on your path.

You can also use the web version directly from unpkg’s CDN: https://unpkg.com/ssim.js@.

📝 Usage

Playground for Node and Web versions.

Node:

import ssim from 'ssim.js';

ssim('./img1.jpg', './img2.jpg')
  .then(({ mssim, performance }) => console.log(`SSIM: ${mssim} (${performance}ms)`))
  .catch(err => console.error('Error generating SSIM', err));

Browser:

  <script src="https://unpkg.com/ssim.js@^2.0.0"></script>
  <script>
    ssim('/img1.jpg', '/img2.jpg')
      .then(function(out) {
        console.log('SSIM:', out.mssim, '(', out.performance, 'ms)');
      })
      .catch(function(err) {
        console.error('Error generating SSIM', err);
      });
  </script>

CLI:

$ ./node_modules/.bin/ssim ./img1.jpg ./img2.jpg

📖 Documentation

If you run into any issues or want a more info, check the wiki.

The code is fully documented and a hosted version is available here.

💡 Rationale

This project is a direct port of algorithms published by Wang, et al. 2004 on “Image Quality Assessment: From Error Visibility to Structural Similarity”. The original Matlab scripts are available here with their datasets. To view the steps taken to validate ssim.js results, check the wiki.