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[YC+06]  Procedural Image Processing for Visualization

Yuan:2006:PIP (In proceedings)
Author(s)Yuan X. and Chen B.
Title« Procedural Image Processing for Visualization »
InAdvances in Visual Computing, Proceedings of the Second International Symposium on Visual Computing, Part 1 (ISVC 2006, November 6--8, 2006, Lake Tahoe, NV, USA)
SeriesLecture Notes in Computer Science
Volume4291
Page(s)50--59
Year2006
PublisherSpringer-Verlag
AddressBerlin · Heidelberg · New York

Abstract
We present a novel Procedural Image Processing (PIP) method and demonstrate its applications in visualization. PIP modulates the sampling positions of a conventional image processing kernel (e.g. edge detection filter) through a procedural perturbation function. When properly designed, PIP can produce a variety of styles for edge depiction, varying on width, solidity, and pattern, etc. In addition to producing artistic stylization, in this paper we demonstrate that PIP can be employed to achieve various visualization tasks, such as contour enhancement, focus+context visualization, importance driven visualization and uncertainty visualization. PIP produces unique effects that often either cannot be easily achieved through conventional filters or would require multiple pass filtering. PIP perturbation functions are either defined by analytical expressions or encoded in pre-generated images. We leverage the programmable fragment shader of the current graphics hardware for achieving the operations in real-time.

BibTeX code
@inproceedings{Yuan:2006:PIP,
  opteditor = {},
  optpostscript = {},
  optorganization = {},
  author = {Xiaoru Yuan and Baoquan Chen},
  optkey = {},
  series = LNICS,
  optannote = {},
  address = SpringerAdr,
  localfile = {papers/Yuan.2006.PIP.pdf},
  optisbn = {},
  publisher = SpringerPub,
  optkeywords = {},
  doi = {http://dx.doi.org/10.1007/11919476_6},
  optmonth = {},
  optciteseer = {},
  opturl = {},
  volume = {4291},
  optcrossref = {},
  optwww = {},
  booktitle = {Advances in Visual Computing, Proceedings of the Second
               International Symposium on Visual Computing, Part 1 (ISVC 2006,
               November 6--8, 2006, Lake Tahoe, NV, USA)},
  optnumber = {},
  abstract = {We present a novel Procedural Image Processing (PIP) method and
              demonstrate its applications in visualization. PIP modulates the
              sampling positions of a conventional image processing kernel (e.g.
              edge detection filter) through a procedural perturbation function.
              When properly designed, PIP can produce a variety of styles for
              edge depiction, varying on width, solidity, and pattern, etc. In
              addition to producing artistic stylization, in this paper we
              demonstrate that PIP can be employed to achieve various
              visualization tasks, such as contour enhancement, focus+context
              visualization, importance driven visualization and uncertainty
              visualization. PIP produces unique effects that often either
              cannot be easily achieved through conventional filters or would
              require multiple pass filtering. PIP perturbation functions are
              either defined by analytical expressions or encoded in
              pre-generated images. We leverage the programmable fragment shader
              of the current graphics hardware for achieving the operations in
              real-time.},
  title = {{P}rocedural {I}mage {P}rocessing for {V}isualization},
  year = {2006},
  pages = {50--59},
}

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