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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)
RBP16 is a guide RNA (gRNA)-binding protein that was shown through immunoprecipitation experiments to interact with approximately 30% of total gRNAs in Trypanosoma brucei mitochondria. To gain insight into the biochemical function of RBP16, we used affinity chromatography and immunoprecipitation to identify RBP16 protein binding partners. By these methods,(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)
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)
Main subject detection (MSD) refers to the task of determining which spatial regions in an image correspond to the most visually relevant or scene-defining object(s) for general viewing purposes. This task, while trivial for a human, remains extremely challenging for a computer. Here, we present an algorithm for MSD which operates by adaptively refining(More)