Image feature enhancement based on the time-controlled total variation flow formulation

Image feature enhancement based on the time-controlled total variation flow formulation

Article history: Received 14 November 2007 Received in revised form 19 June 2008 Available online xxxx Communicated by W. Zhao

Total Variation Based Image and Structure Enhancement for Electron Tomography

To date, it is firmly established that mitochondrial function plays an important role in the regulation of apoptosis (programmed cell death). There is also evidence that defects in function may be related to many of the most common diseases of aging, such as Alzheimer dementia, Parkinson’s disease, type II diabetes mellitus, stroke, atherosclerotic heart disease and cancer. This belief is found...

Adaptive Total Variation Based on Feature Scale

The widely used Total Variation de-noising algorithm can preserve sharp edge, while removing noise. However, since fixed regularization parameter over entire image, small details and textures are often lost in the process. In this paper, we propose a modified Total Variation algorithm to better preserve smaller-scaled features. This is done by allowing an adaptive regularization parameter to co...

Image Denoising Algorithms Based on the Dual Formulation of Total Variation

Image Restoration Based on the Hybrid Total-Variation-Type Model

and Applied Analysis 3 function. Since the edge detector function g : g u0 : 1/ 1 |∇ u0 ∗Gσ x | with Gσ x 1/2πσ2 exp − x2/2σ2 can depict the information of edges, we can employ it as a balance function; that is, we can apply the following model: min u β 2 ‖u − u0‖L2 ∣ ∣1 − gu∣∣BV ∣ ∣gu ∣ ∣ BV 2 1.7 to restore the noisy image 16 . Obviously, | 1 − g u|BV tends to be predominant where edges most ...