Digital Images and Human Vision

By Scott J. Daly. 1993

Subfields: Computer Vision and Pattern Recognition

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Citations in the corpus

Generating Images with Perceptual Similarity Metrics based on Deep Networks (2016, background): “Some prominent examples are the visible differences predictor [9], the spatio-temporal model for moving picture quality assessment [10], and the perceptual distortion metric of Winkler [11].”
Analysis of the Sensitivity Attack against Electronic Watermarks in Images (1998, background): “Particularly because of ongoing developments in perceptual modelling, such solutions tend to di er from implementation to implementation and to improve over time [7].”
Statistical evaluation of image quality measures (2002, background): “However they do not necessarily correspond to all aspects of the observer’s visual perception of the errors, 7,8 nor do they correctly reﬂect structural coding artifacts.”
CAS-CNN: A deep convolutional neural network for image compression artifact suppression (2016, background): “They are known to differ from perceived visual quality [1], [30]–[32] but find wide-spread use due to their simplicity.”
Image database TID 2013 : Peculiarities , results and perspectives (2016, background): “Many visual quality metrics have been exploited in applications such as image and video lossy compression, image denoising, quality control of image printing and scanning, remote sensing, watermarking [2] [3] [4] [5] [6] [7] [8], etc.”
Performance analysis of image compression using wavelets (2001, background): “The HVS is less sensitive to removal of smaller details [ 31 ].”
VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio for Natural Images (2007, background): “…operates under the premise that the HVS has evolved based on the statistical properties of the natural environment, and, therefore, given an original and distorted image, the visual fidelity of the distorted image can be quantified based on the amount of information it provides about the original.”
HDR-VDP-2: a calibrated visual metric for visibility and quality predictions in all luminance conditions (2011, methodology): “The probability summation is computed as in [Daly 1993] After substituting the psychometric function from Equation 17, we get: It is important to note that the product has been replaced by summation.”
Steganalysis using image quality metrics (2003, background): “The incorporation of human visual system (HVS) model into objective measures [25], [26] has led to a better correlation with the subjective ratings in multimedia.”