High resolution Magnetic Resonance (MR) images are desired for accurate diagnostics. In
practice, image resolution is restricted by factors like hardware and processing constraints …

Generative models and inferential autoencoders mostly make use of ℓ _2 norm in their
optimization objectives. In order to generate perceptually better images, this short paper …

High resolution magnetic resonance (MR) images are desired for accurate diagnostics. In
practice, image resolution is restricted by factors like hardware, cost and processing …

Recent studies have demonstrated that the Structural Similarity Index Measure (SSIM) is the
top choice for quantifying both visual quality and image similarity. Although the SSIM is not …

It is now generally accepted that Euclidean-based metrics may not always adequately
represent the subjective judgement of a human observer. As a result, many image …

Literature has shown that Mean Squared Error is not a promising measure for image fidelity
and similarity assessment, and Structural Similarity Index (SSIM) can properly handle this …

This paper studies the one-sided σ-smooth+ concave function maximization problems under
general convex sets. Provided that the objective function is Lipschitz smooth, we use the …

Despite the advances of deep learning in specific tasks using images, the principled
assessment of image fidelity and similarity is still a critical ability to develop. As it has been …

Medical imaging techniques such as magnetic resonance imaging (MRI), computed-
tomography (CT), X-ray, ultra-sound, positron emission tomography (PET), and …