qmeasures: Quality assessment for image reconstructions.

In WIAS-BERLIN/aws: Adaptive Weights Smoothing

Quality assessment for image reconstructions.

Description

Computes selected criteria for quality assessments of

Usage

qmeasures(img, ref,
  which = c("PSNR", "MAE", "MSE", "RMSE", "SSIM", "MAGE", "RMSGE"),
  mask = FALSE)

Arguments

img	2D/3D image, object of class "aws", "ICIsmooth", "kernsm", "nlmeans" or array.
ref	Reference image (array, matrix or vector) for comparison.
which	Criterion to use for Quality assessment. Please specify a subset of "PSNR" (Peak Signal to Noise Ratio), "MAE" (Mean Absolute Error), "MSE" (Mean Squared Error), "RMSE" (Root Mean Squared Error), "SSIM" (Structural SIMilarity), "MAGE" (Mean Absolute Gradient Error), "RMSGE" (Root Mean Squared Gradient Error).
mask	Logical of same dimension as img/ref. Calculation can be restricted to mask.

Details

Calculates specified quality indices.

Value

A vector with names as specified in which.

Author(s)

Joerg Polzehl, [e-mail], https://www.wias-berlin.de/people/polzehl/

WIAS-BERLIN/aws documentation built on Sept. 10, 2023, 6:20 p.m.