| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1784350 | Infrared Physics & Technology | 2014 | 7 Pages |
•The quantitative assessment of image quality by modulation transfer function (MTF).•Graphical description of the sharpness and contrast of an imaging system.•Adaptive neuro-fuzzy system to estimate MTF value of optical system.•Adaptive neuro fuzzy application.
The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the adaptive neuro-fuzzy (ANFIS) estimator is designed and adapted to predict MTF value of the actual optical system. Neural network in ANFIS adjusts parameters of membership function in the fuzzy logic of the fuzzy inference system. The back propagation learning algorithm is used for training this network. This intelligent estimator is implemented using MATLAB/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.
