SSIM
SSIM, or Structural Similarity Index Measure, is a method for assessing the similarity between two images or video frames. It aims to model perceived changes in structural information, as well as luminance and contrast, to provide a metric that better correlates with human visual quality than traditional error measures such as mean squared error or peak signal-to-noise ratio. SSIM was introduced in 2004 by Wang, Bovik, Sheikh, and Simoncelli and has since become widely used in image and video processing tasks, including compression, denoising, and restoration.
The standard SSIM computation compares two images, x and y, using local windows that slide across the
l(x,y) = (2 μx μy + C1) / (μx^2 + μy^2 + C1),
c(x,y) = (2 σx σy + C2) / (σx^2 + σy^2 + C2),
s(x,y) = (σxy + C3) / (σx σy + C3).
The SSIM index for a window is the product l(x,y) · c(x,y) · s(x,y). An SSIM map is formed
Variants and extensions include Multi-Scale SSIM (MS-SSIM), color SSIM, and fast approximations. SSIM is widely used