The geometry of fractals is rich enough that they have extensively been used to model natural phenomena and images. Iterated function systems (IFS) theory provides a convenient way to describe and classify deterministic fractals in the form of a recursive definition. As a result, it is conceivable to develop image representation schemes based on the IFS parameters that correspond to a given fra...

A fast coding algorithm for images using vector quantization (VQ) and pixelwise fractal approximation is proposed. The low frequency component of an input image is approximated and its residual is used to calculate the scaling factor of fractal transform. The scaling factor is compressed by transform VQ (TVQ). In the proposed method, lo encode a digital image by an iterated function system (IFS...

BACKGROUND To report a case of interface fluid syndrome (IFS) following small incision lenticule extraction (SMILE) evaluated with corneal densitometry and optical coherence tomography (OCT). CASE PRESENTATION An 18-year-old man reported sudden vision loss 24 days after SMILE procedure. Intraocular pressure (IOP) was 36.3 mmHg (OD) and 36.7 mmHg (OS) by noncontact tonometry. Moderate corneal ...

OBJECTIVE To determine the radiographic findings of computed tomographic (CT) imaging most suggestive of invasive fungal sinusitis (IFS) in an immunocompromised patient population. DESIGN A retrospective review of patients with a diagnosis of IFS reached with CT and confirmed by histopathologic evaluation. SETTING An academic tertiary care hospital. PATIENTS Twenty-three immunocompromised...

We present an Expectation-Maximization algorithm for the fractal inverse problem: the problem of fitting a fractal model to data. In our setting the fractals are Iterated Function Systems (IFS), with similitudes as the family of transformations. The data is a point cloud in R with arbitrary dimension H. Each IFS defines a probability distribution on R , so that the fractal inverse problem can b...

We investigate the use of iterated function system (IFS) models for data analysis. An IFS is a discrete-time dynamical system in which each time step corresponds to the application of one of the finite collection of maps. The maps, which represent distinct dynamical regimes, may be selected deterministically or stochastically. Given a time series from an IFS, our algorithm detects the sequence ...

In this paper, we present a new feature selection method that is suitable for both unsupervised and supervised problems. We build upon the recently proposed Infinite Feature Selection (IFS) method where feature subsets of all sizes (including infinity) are considered. We extend IFS in two ways. First, we propose a supervised version of it. Second, we propose new ways of forming the feature adja...

We easily tend to think of Integral-Field Spectrographs (IFS) along two opposing trends: as either the beautiful combination between photometry and spectroscopy, or as our worst nightmare including the dark side of both worlds. I favour a view where each IFS is considered individually, as one instrument with specific performances which can be used optimally for a certain range of scientific pro...

One cellular function of intermediate filaments is to provide cells with compliance to small deformations while strengthening them when large stresses are applied. How IFs accomplish this mechanical role is revealed by recent studies of the elastic properties of single IF protein polymers and by viscoelastic characterization of the networks they form. IFs are unique among cytoskeletal filaments...