VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio for Natural Images

• Published in: IEEE transactions on image processing Vol. 16; no. 9; pp. 2284 - 2298
• Main Authors: Chandler, D.M., Hemami, S.S.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.09.2007; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Biomimetics - methods; Computation; Contrast; Detection, estimation, filtering, equalization, prediction; Digital images; Distortion; Distortion measurement; Exact sciences and technology; human visual system (HVS); Humans; Image analysis; Image coding; Image contrast; Image Enhancement - methods; image fidelity; Image Interpretation, Computer-Assisted - methods; Image processing; image quality; Information, signal and communications theory; Mathematical models; Miscellaneous; noise; Object detection; PSNR; Psychology; Reproducibility of Results; Sensitivity and Specificity; Signal and communications theory; Signal processing; Signal to noise ratio; Signal, noise; Telecommunications and information theory; Thresholds; Visual; visual fidelity; Visual Perception - physiology; Visual system; wavelet; Multistage method; image fidelity; visual fidelity; Threshold detection; Computational complexity; Contrast; Image quality; Luminance; Wavelet transformation; Multiscale method; Signal processing; noise; wavelet; Masking; Open market; human visual system (HVS); Signal distortion; Signal to noise ratio; Visual signal; distortion
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2007.901820

This paper presents an efficient metric for quantifying the visual fidelity of natural images based on near-threshold and suprathreshold properties of human vision. The proposed metric, the visual signal-to-noise ratio (VSNR), operates via a two-stage approach. In the first stage, contrast thresholds for detection of distortions in the presence of natural images are computed via wavelet-based models of visual masking and visual summation in order to determine whether the distortions in the distorted image are visible. If the distortions are below the threshold of detection, the distorted image is deemed to be of perfect visual fidelity (VSNR = infin)and no further analysis is required. If the distortions are suprathreshold, a second stage is applied which operates based on the low-level visual property of perceived contrast, and the mid-level visual property of global precedence. These two properties are modeled as Euclidean distances in distortion-contrast space of a multiscale wavelet decomposition, and VSNR is computed based on a simple linear sum of these distances. The proposed VSNR metric is generally competitive with current metrics of visual fidelity; it is efficient both in terms of its low computational complexity and in terms of its low memory requirements; and it operates based on physical luminances and visual angle (rather than on digital pixel values and pixel-based dimensions) to accommodate different viewing conditions.