The total variation based image denoising model of Rudin, Osher, and Fatemi has been generalized and modified in many ways in the literature; one of these modifications is to use the L1 norm as the fidelity term. We study the interesting consequences of this modification, especially from the point of view of geometric properties of its solutions. It turns out to have interesting new implication...

The problem of blindly assessing the quality of visual signals – without reference, and without assuming a single distortion type – has long been regarded as, if not impossible, perhaps too difficult to bother with. After all, it requires sorting out the black box we call the visual apparatus of the human brain, which despite an increased level of transparency over the past 40 years, remains po...

Two computationally efficient methods for superresolution reconstruction and restoration of microscanning imaging systems are presented. Microscanning creates multiple low-resolution images with slightly different sample-scene phase shifts. The digital processing methods developed here combine the low-resolution images to produce an image with higher pixel resolution (i.e., superresolution) and...

Human pose estimation is the task of estimating the ‘pose’ or configuration of a person’s body parts e.g. labeling the position and orientation of the head, torso, arms and legs in an image. In this paper we propose an extension of the pictorial structure model (PSM) approach [2]. Our method incorporates richer models of appearance and prior over pose without introducing unacceptable computatio...

Introduction: This paper details an evaluation of the implementation and feasibility of a multilevel project entitled Kin KeeperSM Cancer Prevention Intervention that utilizes community health workers (CHWs) to deliver breast and cervical cancer education. The evaluation includes intervention fidelity, participant satisfaction, participant retention, and the cost of program implementa...

The goal of quality assessment (QA) research is to design algorithms that can automatically assess the quality of images in a perceptually consistent manner. Image QA algorithms generally interpret image quality as fidelity or similarity with a “reference” or “perfect” image in some perceptual space. In order to improve the assessment accuracy of white noise, Gauss blur, JPEG2000 compression an...