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

N. Kiryati; A. Bruckstein

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

N. Kiryati^*, A. Bruckstein

^*Corresponding author for this work

Technion-Israel Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

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 language	English
Title of host publication	Proc CVPR 88 Comput Soc Conf on Comput Vision and Pattern Recognit
Publisher	Publ by IEEE
Pages	562-567
Number of pages	6
ISBN (Print)	0818608625
State	Published - 1988
Externally published	Yes

Publication series

Name	Proc CVPR 88 Comput Soc Conf on Comput Vision and Pattern Recognit

Funding

Funders	Funder number
Foundation for Research in Electronics, Computers and Communications
Israel Academy of Sciences and Humanities

Cite this

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title = "Gray-levels can improve the performance of binary image digitizers.",

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.",

author = "N. Kiryati and A. Bruckstein",

note = "Funding Information: {\textquoteright} This research was supported in part by the Foundation for Research in Electronics, Computers and Communications, administered by The Israel Academy of Sciences and Humanities.",

year = "1988",

language = "אנגלית",

isbn = "0818608625",

series = "Proc CVPR 88 Comput Soc Conf on Comput Vision and Pattern Recognit",

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}

Gray-levels can improve the performance of binary image digitizers. / Kiryati, N.; Bruckstein, A.
Proc CVPR 88 Comput Soc Conf on Comput Vision and Pattern Recognit. Publ by IEEE, 1988. p. 562-567 (Proc CVPR 88 Comput Soc Conf on Comput Vision and Pattern Recognit).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Bruckstein, A.

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PY - 1988

Y1 - 1988

N2 - 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.

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BT - Proc CVPR 88 Comput Soc Conf on Comput Vision and Pattern Recognit

PB - Publ by IEEE

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

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