Image Enhancement by Stochastic Homomorphic Filtering

Robert W. Fries, James W. Modestino

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

The problem of image enhancement by nonlinear two-dimensional (2-D) homomorphic filtering is approached using stochastic models of the signal and degradations. Homomorphic filtering has been previously used for image enhancement, but the linear filtering operation has generally been chosen heuristically. In this paper stochastic image models previously described are used to model the true image and interfering components (shadows and salt-and-pepper noise). The problem of designing the linear filter can then be formulated as one of linear least mean-squared error (Wiener) filtering. Examples of processing of typical real-world images are included.

Original languageEnglish (US)
Pages (from-to)625-637
Number of pages13
JournalIEEE Transactions on Acoustics, Speech, and Signal Processing
Volume27
Issue number6
DOIs
StatePublished - Dec 1979

ASJC Scopus subject areas

  • Signal Processing

Fingerprint Dive into the research topics of 'Image Enhancement by Stochastic Homomorphic Filtering'. Together they form a unique fingerprint.

  • Cite this