DocumentCode :
960241
Title :
Imaging below the diffraction limit: a statistical analysis
Author :
Shahram, Morteza ; Milanfar, Peyman
Author_Institution :
Dept. of Electr. Eng., Univ. of California, Santa Cruz, CA, USA
Volume :
13
Issue :
5
fYear :
2004
fDate :
5/1/2004 12:00:00 AM
Firstpage :
677
Lastpage :
689
Abstract :
The present paper is concerned with the statistical analysis of the resolution limit in a so-called "diffraction-limited" imaging system. The canonical case study is that of incoherent imaging of two closely-spaced sources of possibly unequal brightness. The objective is to study how far beyond the classical Rayleigh limit of resolution one can reach at a given signal to noise ratio. The analysis uses tools from statistical detection and estimation theory. Specifically, we will derive explicit relationships between the minimum detectable distance between two closely-spaced point sources imaged incoherently at a given SNR. For completeness, asymptotic performance analysis for the estimation of the unknown parameters is carried out using the Crame´r-Rao bound. To gain maximum intuition, the analysis is carried out in one dimension, but can be well extended to the two-dimensional case and to more practical models.
Keywords :
diffraction; image resolution; optical images; statistical analysis; Cramer-Rao bound; SNR; asymptotic performance analysis; classical Rayleigh limit; closely-spaced sources; diffraction limited imaging system; estimation theory; hypothesis test; incoherent imaging; minimum detectable distance; signal to noise ratio; statistical detection; Additive noise; Brightness; Image resolution; Noise measurement; Optical diffraction; Optical imaging; Signal resolution; Signal to noise ratio; Spatial resolution; Statistical analysis; Algorithms; Computer Simulation; Data Compression; Image Enhancement; Image Interpretation, Computer-Assisted; Models, Statistical; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2004.826096
Filename :
1288193
Link To Document :
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