Objective measures of image quality generally operate by comparing pixels of a “degraded”
image to those of the original. Relative to human observers, these measures are overly …

Performance of blind image quality assessment (BIQA) models has been significantly
boosted by end-to-end optimization of feature engineering and quality regression …

The performance of objective image quality assessment (IQA) models has been evaluated
primarily by comparing model predictions to human quality judgments. Perceptual datasets …

Exposure bracketing is crucial to high dynamic range imaging, but it is prone to halos for
static scenes and ghosting artifacts for dynamic scenes. The recently proposed structural …

In most practical situations, the compression or transmission of images and videos creates
distortions that will eventually be perceived by a human observer. Vice versa, image and …

Exemplar-based colorization is a challenging task, which attempts to add colors to the target
grayscale image with the aid of a reference color image, so as to keep the target semantic …

Computational models for blind image quality assessment (BIQA) are typically trained in well-
controlled laboratory environments with limited generalizability to realistically distorted …

We develop a method for comparing hierarchical image representations in terms of their
ability to explain perceptual sensitivity in humans. Specifically, we utilize Fisher information …

Decoding sensory stimuli from neural signals can be used to reveal how we sense our
physical environment, and is valuable for the design of brain-machine interfaces. However …

Omnidirectional images (also referred to as static 360 panoramas) impose viewing
conditions much different from those of regular 2D images. How do humans perceive image …