Gray-levels can improve the performance of binary image digitizers.

N. Kiryati, A. Bruckstein

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The application of gray-scale digitizers to the digitization of binary images of straight-edged silhouettes is considered. A measure of digitization-induced ambiguity is introduced. It is shown that if the gray levels are not quantized and the sampling resolution is sufficiently high, error-free reconstruction of the original binary image from the digitized image is possible. When the total bit-count for the representation of the digitized image is limited, i.e., sampling resolution and quantization accuracy are both finite, error-free reconstruction is usually impossible. The authors' suggested bit allocation policy is then to increase the quantization accuracy as much as possible, once sufficient sampling resolution has been reached.

Original languageEnglish
Title of host publicationProc CVPR 88 Comput Soc Conf on Comput Vision and Pattern Recognit
PublisherPubl by IEEE
Pages562-567
Number of pages6
ISBN (Print)0818608625
StatePublished - 1988
Externally publishedYes

Publication series

NameProc CVPR 88 Comput Soc Conf on Comput Vision and Pattern Recognit

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