DocumentCode :
3239018
Title :
Modulation transfer function and noise measurement using neural networks
Author :
Delvit, Jean-Marc ; Léger, Dominique ; Roques, Sylvie ; Valorge, Christophe
Author_Institution :
ONERA, France
fYear :
2003
fDate :
17-19 Sept. 2003
Firstpage :
131
Lastpage :
140
Abstract :
In the context of Earth observation satellites such as SPOT or IKONOS, it is important to measure the modulation transfer function (MTF) and the noise in order to quantify the quality of the imaging system. This measurement is useful to decide to focus the telescope or to make a deconvolution filter whose purpose is to enhance image contrast. This paper presents a univariant MTF and noise measurement method using non specific views. It is a particular application of a general approach of image quality assessment. The method presented in this paper is based on artificial neural network (ANN) use. The ANN learns how to recognize MTF and noise from known images, and the neural network is able, after the learning step, to assess the MTF and the noise from unknown images.
Keywords :
deconvolution; geophysical signal processing; geophysical techniques; image processing; neural nets; noise measurement; optical transfer function; satellite communication; Earth observation satellites; artificial neural network; deconvolution filter; image quality assessment; imaging system; modulation transfer function; noise measurement; Artificial neural networks; Artificial satellites; Deconvolution; Filters; Focusing; Image quality; Neural networks; Noise measurement; Telescopes; Transfer functions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks for Signal Processing, 2003. NNSP'03. 2003 IEEE 13th Workshop on
ISSN :
1089-3555
Print_ISBN :
0-7803-8177-7
Type :
conf
DOI :
10.1109/NNSP.2003.1318011
Filename :
1318011
Link To Document :
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