PSNR

Core and matricesfunctionOpenCV 5.0.0

import { PSNR } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

Explore visually: PSNR and SSIM quality metrics →

Measure selected differences or quality cues between images, or estimate quality without a reference.

VISUAL WALKTHROUGHSimilarity

REFERENCE INPUTReference image

Compare aligned images with the same numeric range.

→

RESULTAggregate the error

These values are computed from the displayed 16 × 12 arrays. SSIM and other perceptual metrics use different definitions.

Computed MSE and PSNR example. Scalar error metrics summarize a spatial difference; they do not explain perceptual quality by themselves.

Computes the Peak Signal-to-Noise Ratio (PSNR) image quality metric.

This function calculates the Peak Signal-to-Noise Ratio (PSNR) image quality metric in decibels (dB), between two input arrays src1 and src2. The arrays must have the same type.

The PSNR is calculated as follows:

\texttt{PSNR} = 10 \cdot \log_{10}{\left( \frac{R^2}{MSE} \right) }

where R is the maximum integer value of depth (e.g. 255 in the case of CV_8U data) and MSE is the mean squared error between the two arrays.

PSNR(src1: Mat, src2: Mat, R: number): number;

2 available overloads

PSNR(src1: Mat, src2: Mat): number;

PSNR(src1: Mat, src2: Mat, R: number): number;

src1

first input array.

src2

second input array of the same size as src1.

R

the maximum pixel value (255 by default)

Returns

The number result.

Upstream declaration ↗

These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.