Image SSIM is a TypeScript/JavaScript library for calculating the Structural Similarity (SSIM) index between two images, suitable for both browser and server environments. This metric aims to quantify perceived image quality and similarity more effectively than traditional methods like PSNR or MSE, by focusing on structural information. Currently at version 0.2.0, this package is relatively stable for its core functionality, though its low version number suggests it may not receive frequent major feature updates or breaking changes typical of rapidly evolving libraries. Its key differentiator is providing a straightforward, cross-platform implementation of the SSIM algorithm, based on established references in the field. It is designed for developers needing a perceptual image comparison tool without heavy external dependencies. While the `npm` package `img-ssim` offers similar functionality, it uses image paths/URLs and callbacks, whereas `image-ssim` expects raw `ImageData`-like objects and returns a Promise or direct value, making `image-ssim` more suitable for in-memory image processing workflows.
npm install image-ssimVerified import paths — ran on the pinned version, not inferred.
Demonstrates how to calculate the SSIM between two mock ImageData objects, including a case for identical images and a case for differing images, and handles dimension mismatch.
Always pin to an exact version or use a lockfile to ensure stability in production environments. Review the GitHub repository for any recent activity or unreleased changes.
Ensure input images are properly pre-processed into `ImageData` objects or objects mimicking its structure, especially if handling images from different sources (e.g., Node.js buffers vs. browser canvas data).
Be aware that SSIM might not capture all aspects of perceived quality for color images. For critical applications, consider explicitly converting images to a luminance channel before calculation or exploring more advanced multi-scale or color-aware image quality metrics like MS-SSIM or DSSIM for improved perceptual accuracy.
For performance-critical applications, consider downsampling images before SSIM calculation, optimizing the image loading/processing pipeline, or offloading calculations to Web Workers in the browser or separate processes in Node.js. Benchmarking with representative image sizes is recommended.
If comparing results with other SSIM tools or research papers, verify the specific algorithm, parameters (e.g., window size, constants), and color space conversion used by each implementation. Consistency is best achieved by using the same library throughout your project.
Ensure both input `ImageData` objects have identical `width` and `height` properties before calling `ssim`. Resize one or both images if necessary, although resizing can introduce its own artifacts that affect SSIM.
Verify that both arguments passed to `ssim` are valid `ImageData` objects or objects structurally identical to `ImageData`, specifically having `data: Uint8ClampedArray`, `width: number`, and `height: number` properties.
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