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2D NMR: Overview of Heteronuclear Correlation Techniques01:18

2D NMR: Overview of Heteronuclear Correlation Techniques

Heteronuclear correlation spectroscopy is an analytical technique that investigates the coupling between different types of nuclei, often a proton and an X-nucleus, such as carbon-13 or nitrogen-15. This method is commonly used in nuclear magnetic resonance (NMR) spectroscopy to gain insights into complex chemical compounds' structural and compositional aspects. A typical heteronuclear correlation spectrum displays X-nucleus chemical shifts on one axis and a proton spectrum on the other axis.
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Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
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Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...
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An infinite series composed of positive terms may either approach a finite value or increase without bound. Determining which outcome occurs is a central task in calculus, and comparison tests provide structured methods for making this determination. Rather than evaluating a series directly, these tests relate it to another series whose behavior is already known, allowing conclusions to be drawn through logical comparison.The direct comparison test applies to series with positive terms. If each...
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Fast full-search equivalent template matching by enhanced bounded correlation.

S Mattoccia1, F Tombari, L Di Stefano

  • 1Dipartimento di Elettronica, Informatica e Sistemistica, University of Bologna, Bologna, Italy. steffano.mattoccia@unibo.it

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|April 9, 2008
PubMed
Summary

We introduce an Enhanced Bounded Correlation (EBC) algorithm for faster template matching using normalized cross correlation (NCC). EBC significantly reduces computations while maintaining accuracy, outperforming existing methods.

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Area of Science:

  • Computer Vision
  • Image Processing
  • Algorithm Development

Background:

  • Template matching is crucial in image analysis.
  • Normalized Cross Correlation (NCC) is a standard but computationally intensive method.
  • Existing algorithms often require extensive computation or parameter tuning.

Purpose of the Study:

  • To develop a computationally efficient template matching algorithm.
  • To achieve results equivalent to full search NCC without the high computational cost.
  • To create a parameter-free algorithm with competitive performance.

Main Methods:

  • Proposed Enhanced Bounded Correlation (EBC) algorithm.
  • Utilized bounding functions based on Cauchy-Schwarz inequality to prune search space.
  • Incorporated an online parameter prediction step for a parameter-free approach.

Main Results:

  • EBC significantly reduces computations for NCC template matching.
  • The algorithm yields identical results to full search methods.
  • EBC demonstrates computational advantages comparable to offline parameter tuning.
  • Experimental results show superior performance over state-of-the-art methods.

Conclusions:

  • EBC offers a substantial acceleration for template matching tasks.
  • The parameter-free nature of EBC enhances its practical applicability.
  • The proposed method represents a significant advancement in efficient image template matching.