Reconstruction of Binary Images,
Abstract
We consider the following problem: a black and white image is observed in digitized form. Unfortunately the 'real' image is not observed: at some stage the image has been distorted with noise. Our objective is to remove as much of the noise as possible, to get approximately the original image back. In a more mathematical setting, let x be an m by n array, with entries 0 and 1; x is considered to be a realization of a random variable X. We do not observe the image x. Instead we observe y, a noisy version of x that is a realization of the random variable Y, where the distribution of Y depends on x. We want to estimate x on the basis of y.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1992
- Accession Number
- ADP007217
Entities
People
- Charles Kooperberg
Organizations
- University of California, Berkeley