The Problem Of Super Resolution

"This course is intended to highlight mathematical principles, concepts, and techniques that are often used in scientific applications and illustrate how these techniques are employed in the context of specific problems in physics, chemistry, and biology. Topics include mathematical

The model parameters are estimated from the EP and therefore the AR can be calculated within the TP (Strong, 1992). Explicitly, the AR which

the network parameters associated with xt and ht−1 respectively. φ is a nonlinear function which we can choose from

If a sample surface has height variations a fully focused image can be obtained instantaneously by bringing together images taken over a range of focal planes. This focal position data can then be used to produce a three-dimensional model.

To predict the behavior of a physical system governed by a complex mathematical model depends on un- derlying model parameters. For example, predicting the contaminant transport or oil production strongly influenced by subsurface properties, such as permeability, porosity and other spatial fields. These spatial fields are highly heterogeneous and vary over a rich hierarchy of scales, which makes the forward models

When the real sharp image is not known, we are faced with the problem of finding

Daftardar-Gejji and Jafari [17] have introduced a new iterative method (NIM) which is simple to

To address the understanding of current techniques, we shall dissect several papers, past and present to reveal the pros and cons of each of the core techniques and models, employed within the scope of this Thesis.

This technique requires to perform sensitivity analysis (please refer to page 12 for FCFF assumption and page 14 for sensitivity

“The quantitative way of relating the object distance d-sub o with the image distance d-sub i for a lens given by the then-lens equation (1/d-sub o)+(1/d-sub i)=1/f. Rearrange to show that d-sub i=(d-sub o)(f)/(d-sub o)-(f)”

analysis that is discussed in later sections of this paper. Then, roughly speaking, the goal of output-data

Ch. 10). In this paper I will address how I will refine some solutions in regards to the issue at

In scientific imaging where spatial correlation is more important than intensity of signal (such as separating DNA fragments of quantized length), the small signal to noise

1989). The difference betwe en the two approaches can be viewed in ter ms of

This representation of Haar-Like Feature was used to find and select features according to pixel intensities and not by pixels values. Haar-like feature can be calculated using the scalar product between the input image and some Haar-like templates [14].