Structural similarity index measure

A method for predicting the perceived quality of digital television and cinematic pictures, as well as other kinds of digital images and videos.

The structural similarity index measure is a method for predicting the perceived quality of digital television and cinematic pictures, as well as other kinds of digital images and videos. SSIM is used for measuring the similarity between two images. The SSIM index is a full reference metric; in other words, the measurement or prediction of image quality is based on an initial uncompressed or distortion-free image as a reference.

SSIM is a perception-based model that considers image degradation as perceived change in structural information, while also incorporating important perceptual phenomena, including both luminance masking and contrast masking terms. The difference with other techniques such as MSE or PSNR is that these approaches estimate absolute errors. Structural information is the idea that the pixels have strong inter-dependencies especially when they are spatially close. These dependencies carry important information about the structure of the objects in the visual scene. Luminance masking is a phenomenon whereby image distortions (in this context) tend to be less visible in bright regions, while contrast masking is a phenomenon whereby distortions become less visible where there is a significant activity or "texture" in the image.

acronymn
  • SSIM
resources
  • Structural Similarity Measure for Color Images on ijcaonline.org
  • A Formal Assessment of the Structural Similarity Index on uregina.ca
  • How to calculate the Structural Similarity Index (SSIM) between two images with Python on ourcodeworld.com
  • ssim on mathworks.com
  • All about Structural Similarity Index (SSIM): Theory + Code in PyTorch on medium.com
source
Adapted from content published on wikipedia.org
Last modified on May 30, 2021, 2:14 am
Videocide.com is a service provided by Codecide, a company located in Chicago, IL USA.
magnifier