Detail publikace

Complex-Valued Wavelets for Edge Enhancement in Medical Images

Originální název

Complex-Valued Wavelets for Edge Enhancement in Medical Images

Anglický název

Complex-Valued Wavelets for Edge Enhancement in Medical Images

Jazyk

en

Originální abstrakt

It is often needed to accurately expand images without loss of clarity in a number of medical image processing applications. Traditional methods such as bilinear interpolation and cubic spline interpolation tend to smooth out edge regions and result in blurry images. To deblur the expanded images one could use the approach of unsharp masking, other methods include modeling the edges or filtering with nonlinear filters. The development of enhancement techniques for medical imaging is highly influenced by strong requirements: (1) diagnostic quality of images should be kept, (2) no disturbing information should be added, and (3) the image processing should be fast. Also, the problem of zooming-in is further specified by the requirement of preserving sharp edges.

Anglický abstrakt

It is often needed to accurately expand images without loss of clarity in a number of medical image processing applications. Traditional methods such as bilinear interpolation and cubic spline interpolation tend to smooth out edge regions and result in blurry images. To deblur the expanded images one could use the approach of unsharp masking, other methods include modeling the edges or filtering with nonlinear filters. The development of enhancement techniques for medical imaging is highly influenced by strong requirements: (1) diagnostic quality of images should be kept, (2) no disturbing information should be added, and (3) the image processing should be fast. Also, the problem of zooming-in is further specified by the requirement of preserving sharp edges.

BibTex


@inproceedings{BUT5642,
  author="Petr {Fedra} and Ivo {Provazník}",
  title="Complex-Valued Wavelets for Edge Enhancement in Medical Images",
  annote="It is often needed to accurately expand images without loss of clarity in a number of medical image processing applications. Traditional methods such as bilinear interpolation and cubic spline interpolation tend to smooth out edge regions and result in blurry images. To deblur the expanded images one could use the approach of unsharp masking, other methods include modeling the edges or filtering with nonlinear filters.
The development of enhancement techniques for medical imaging is highly influenced by strong requirements: (1) diagnostic quality of images should be kept, (2) no disturbing information should be added, and (3) the image processing should be fast. Also, the problem of zooming-in is further specified by the requirement of preserving sharp edges.",
  address="Verlag der Technischen Universitat Graz, Austria",
  booktitle="IFMBE Proceedings - 2nd European Medical and Biological Engineering Conference EMBEC'02",
  chapter="5642",
  institution="Verlag der Technischen Universitat Graz, Austria",
  year="2002",
  month="december",
  pages="950",
  publisher="Verlag der Technischen Universitat Graz, Austria",
  type="conference paper"
}