Experiments with an adaptive Bayesian restoration method

Domenico Tegolo, Maria Concetta Maccarone

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This paper describes a Bayesian restoration method applied to two-dimensional measured images, whose detector response function is not completely known. The response function is assumed Gaussian with standard deviation depending on the estimate of the local density of the image. The convex hull of the K-nearest neighbours (KNN) of each 'on' pixel is used to compute the local density. The method has been tested on 'sparse' images, with and without noise background. © 1989.
Original languageEnglish
Pages (from-to)289-296
Number of pages8
JournalPattern Recognition Letters
Volume10
Publication statusPublished - 1989

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Experiments with an adaptive Bayesian restoration method'. Together they form a unique fingerprint.

Cite this