Image detection under low-level illumination

Author

Sequeira, Raúl E. ; Gubner, John A. ; Saleh, Bahaa E A

Author_Institution

Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA

Volume

2

Issue

1

fYear

1993

fDate

1/1/1993 12:00:00 AM

Firstpage

18

Lastpage

26

Abstract

Image detection under low-light-level conditions is treated as a hypothesis-testing problem in which the observations are modeled as a shot-noise process. Since computing the likelihood ratio for shot-noise processes is not feasible, the use of a one-dimensional test statistic obtained by filtering and sampling the observations is proposed. The filter is chosen to maximize a generalized signal-to-noise ratio. The likelihood ratio for the one-dimensional test statistic is evaluated numerically by inverting the corresponding characteristic function under each hypothesis

Keywords

filtering and prediction theory; image processing; random noise; filtering; generalized signal-to-noise ratio; hypothesis-testing problem; image detection; likelihood ratio; low-level illumination; low-light-level conditions; one-dimensional test statistic; sampling; shot-noise process; Face detection; Filtering; Image sampling; Lighting; Nonlinear filters; Optical imaging; Random variables; Signal to noise ratio; Statistical analysis; Testing;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.210862

Filename

210862