Search Results for "variation"

ColorI-DT (Color Image Difference Tool): Colori-DT is an open-source tool developed in MATLAB and designed to measure color differences in images. It is intended to provide researchers and professionals with an accurate and user-friendly means of assessing color variation and discrepancies in digital images according to different metrics. Contacts: Filippo Piccinini (emails: filippo.piccinini@irst.emr.it; f.piccinini@unibo.it) Repository: https://sourceforge.net/p/colori-dt/ How to cite us when using the tool: Filippo Piccinini et al. “Colori-DT: an open-source tool for the quantitative evaluation of differences in microscopy color images”.

Library for continuous convex optimization in image analysis, together with a command line tool and Matlab interface. Implements several recent algorithms for inverse problems and image segmentation with total variation regularizers and vectorial multilabel transition costs. Also included is a suite for variational light field analysis, which ties into the HCI light field benchmark set and givens reference implementations for a number of our recently published algorithms. *** NOTE: documentation on the SourceForge page is outdated and not updated anymore, please visit http://cocolib.net ***

...Models are represented in Zinc as mathematical fields defined over domains, including finite elements with support for high-order basis functions, complex parameter mappings and time variation, and image-based fields. Further fields can be defined by mathematical expressions and algorithms on existing fields, including image processing filters. Zinc model data structures are dynamic, supporting interactive applications which programmatically create, destroy and modify parts of models.

Algorithms based on Total Variation (TV) minimization are prevalent in image processing. They play a key role in a variety of applications such as image denoising, compressive sensing and inverse problems in general. In this work, we extend the TV dual framework that includes Chambolle's and Gilboa-Osher's projection algorithms for TV minimization. We use a flexible graph data representation that allows us to generalize the constraint on the projection variable.