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The mainstream approach to image quality assessment has centered around accurately modeling the single most relevant strategy employed by the human visual system (HVS) when judging image quality (e.g., detecting visible differences, and extracting image structure/information). In this work, we suggest that a single strategy may not be sufficient; rather, we(More)
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(More)
In this section, the performance of the VSNR metric is analyzed in terms of its ability to predict fidelity in a manner that agrees with subjective ratings, and in terms of its computational and memory requirements. To assess the predictive performance of the VSNR metric, a psychophysical scaling experiment was performed on various distorted images to(More)
It is widely known that the wavelet coefficients of natural scenes possess certain statistical regularities which can be affected by the presence of distortions. The DIIVINE (Distortion Identification-based Image Verity and Integrity Evaluation) algorithm is a successful no-reference image quality assessment (NR IQA) algorithm, which estimates quality based(More)
Natural scenes, like most all natural data sets, show considerable redundancy. Although many forms of redundancy have been investigated (e.g., pixel distributions, power spectra, contour relationships, etc.), estimates of the true entropy of natural scenes have been largely considered intractable. We describe a technique for estimating the entropy and(More)
— In this paper, we present a simple, yet effective wavelet-based algorithm for estimating both global and local image sharpness (FISH, Fast Image Sharpness). FISH operates by first decomposing the input image via a three-level separable discrete wavelet transform (DWT). Next, the log-energies of the DWT subbands are computed. Finally, a scalar index(More)
We propose an efficient blind/no-reference image quality assessment algorithm using a log-derivative statistical model of natural scenes. Our method, called DErivative Statistics-based QUality Evaluator (DESIQUE), extracts image quality-related statistical features at two image scales in both the spatial and frequency domains. In the spatial domain,(More)
The additivity of wavelet subband quantization distortions was investigated in an unmasked detection task and in masked detection and discrimination tasks. Contrast thresholds were measured for both simple targets (artifacts induced by uniform quantization of individual discrete wavelet transform subbands) and compound targets (artifacts induced by uniform(More)
This paper presents an algorithm for video quality assessment , spatiotemporal MAD (ST-MAD), which extends our previous image-based algorithm (MAD [1]) to take into account visual perception of motion artifacts. ST-MAD employs spatiotemporal " images " (STS images [2]) created by taking time-based slices of the original and distorted videos. Motion(More)
This paper presents the results of two psychophysical experiments and an associated computational analysis designed to quantify the relationship between visual salience and visual importance. In the first experiment, importance maps were collected by asking human subjects to rate the relative visual importance of each object within a database of(More)