CHARACTERIZING DIGITAL IMAGE ACQUISITION DEVICES

被引:206
作者
REICHENBACH, SE
PARK, SK
NARAYANSWAMY, R
机构
[1] SCI & TECHNOL CORP,HAMPTON,VA 23666
[2] COLL WILLIAM & MARY,DEPT COMP SCI,WILLIAMSBURG,VA 23185
关键词
IMAGE FORMATION; IMAGE RESTORATION; MODULATION TRANSFER FUNCTION; OPTICAL TRANSFER FUNCTION; POINT SPREAD FUNCTION; EVALUATION TECHNOLOGY; IMAGE ACQUISITION DEVICES; SAMPLING;
D O I
10.1117/12.55783
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Despite the popularity of digital imaging devices (e.g., CCD array cameras) the problem of accurately characterizing the spatial frequency response of such systems has been largely neglected in the literature. This paper describes a simple method for accurately estimating the optical transfer function of digital image acquisition devices. The method is based on the traditional knife-edge technique but explicitly deals with fundamental sampled system considerations: insufficient and anisotropic sampling. Results for both simulated and real imaging systems demonstrate the accuracy of the method.
引用
收藏
页码:170 / 177
页数:8
相关论文
共 24 条
[1]   LINE SPREAD FUNCTION + CUMULATIVE LINE SPREAD FUNCTION FOR SYSTEMS WITH ROTATIONAL SYMMETRY [J].
BARAKAT, R ;
HOUSTON, A .
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA, 1964, 54 (06) :768-&
[3]   THOMSON-CSF FRAME-TRANSFER CHARGE-COUPLED-DEVICE IMAGERS - DESIGN AND EVALUATION AT VERY LOW FLUX LEVEL [J].
BEAL, G ;
BOUCHARLAT, G ;
CHABBAL, J ;
DUPIN, JP ;
FORT, B ;
MELLIER, Y .
OPTICAL ENGINEERING, 1987, 26 (09) :902-910
[4]  
Blackman E.S., 1969, P SOC PHOTO-OPT INS, V0016, P105, DOI [10.1117/12.946802, DOI 10.1117/12.946802]
[5]  
Hamming R., 1983, DIGITAL FILTERS
[6]   METHODS FOR ENGINEERING PHOTOGRAPHIC SYSTEMS [J].
HIGGINS, GC .
APPLIED OPTICS, 1964, 3 (01) :1-&
[7]  
Hopwood R. K., 1980, Proceedings of the Society of Photo-Optical Instrumentation Engineers, V230, P72
[8]  
JONES RA, 1969, PHOTOGR SCI ENG, V13, P200
[9]  
JONES RA, 1987, PHOTOG SCI ENG, V11, P102
[10]  
Mazumdar M., 1985, Proceedings CVPR '85: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No. 85CH2145-1), P27