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Peak Signal-to-Noise Ratio (PSNR) measures the peak error between the original and a compressed image. Used to assess the quality of reconstructed images.

Mean Squared Error (MSE) is the average of the squared differences between the original and compressed images. Used to quantify the image quality degradation.

Structural Similarity Index (SSIM) compares local patterns of pixel intensities of predicted and reference images. Used for measuring the perceived quality of digital images.

Root Mean Squared Error (RMSE) is the square root of the MSE and provides a measure of the differences between values predicted by a model or an estimator and the values observed. Used in image fusion and reconstruction quality assessment.

Mean Absolute Error (MAE) measures the average magnitude of the errors in a set of predictions, without considering their direction. Used to summarize the errors in a predictive model.

Universal Image Quality Index (UIQI) assesses the quality of an image by measuring three factors: loss of correlation, luminance distortion, and contrast distortion. Used for quality assessment in image processing.

Visual Information Fidelity (VIF) metric quantifies how much visual information is shared between a reference and a distorted image. Used when visual fidelity is the main concern.

Feature Similarity Index (FSIM) measures the similarity between two images based on low-level features. Used to compare the quality of images with reference to structural details.

Mean Absolute Deviation (MAD) is a measure of the average deviation of data points from their mean. Used to summarize the spread or variability in a data set.