2D linear systems (general imaging system, linearity definition, superpositional integral, delta function, impulse response, spatial invariance, convolution, zoom). 2D Fourier transform (integral record, 2D DFT, selected properties of the 2D FT ? spectra display, separability, translation, periodicity and associated symmetry, rotation, distributivity, scale, average value, convolution, correlation). Fourier transform in higher dimensions. Frequency domain. Fundamental principles of 2D Discrete Cosine Transform (DCT), Hough transform and Radon transform. System transfer function. Mathematical theory of optical transfer function (OTF, MTF, PSF, LSF, ESF and their relationships). MTF and OTF importance in optical and electro-optical systems particularly from the image quality point of view. OTF measurement methods. Image sensors MTF measurement methods. Electro-optical systems transfer characteristics. Total MTF of the image systems. Linear filters including cascade of linear filters. Deconvolution. Inverse filters. Wiener filter. Blind deconvolution principle. Examples of use (blur correction). OTF and deconvolution context (2D, 3D, 4D). Image sampling process. Image sampling theorem. Aliasing. Aperture effect. Image sensors modeling and simulation. Models of image sensors based on the unequal spatial sampling. Possibilities of experiments including real image sensors. State of the art and trends of the present development of imaging systems. Summary of fundamental knowledge within the course.
Contents:
2D linear systems (general imaging system, linearity definition, superpositional integral, delta function, impulse response, spatial invariance, convolution, zoom). 2D Fourier transform (integral record, 2D DFT, selected properties of the 2D FT ? spectra display, separability, translation, periodicity and associated symmetry, rotation, distributivity, scale, average value, convolution, correlation). Fourier transform in higher dimensions. Frequency domain. Fundamental principles of 2D Discrete Cosine Transform (DCT), Hough transform and Radon transform. System transfer function. Mathematical theory of optical transfer function (OTF, MTF, PSF, LSF, ESF and their relationships). MTF and OTF importance in optical and electro-optical systems particularly from the image quality point of view. OTF measurement methods. Image sensors MTF measurement methods. Electro-optical systems transfer characteristics. Total MTF of the image systems. Linear filters including cascade of linear filters. Deconvolution. Inverse filters. Wiener filter. Blind deconvolution principle. Examples of use (blur correction). OTF and deconvolution context (2D, 3D, 4D). Image sampling process. Image sampling theorem. Aliasing. Aperture effect. Image sensors modeling and simulation. Models of image sensors based on the unequal spatial sampling. Possibilities of experiments including real image sensors. State of the art and trends of the present development of imaging systems. Summary of fundamental knowledge within the course.
Recommended literature:
Required:
[1] Image sensing, acquisition and processing course in microscopy [online]. Jiří Hozman, c2002-2017. Last change 18. 10. 2013 [cit. 2017-09-27]. URL: http://webzam.fbmi.cvut.cz/hozman/
[2] Webster, J. G. (ed.). Wiley Encyclopedia of Medical Devices and Instrumentation. 2000. Available within EIS of CTU: http://knihovna.cvut.cz/ . [cit. 2017-09-27].
[3] Hozman, J., Roubík, K. Tomografical imaging methods in medicine - CT. Education videoprogram. Prague: AVTC CTU, 2002. Available from http://www.civ.cvut.cz/info/info.php?did=603
Recommended:
[4] DRASTICH, Aleš. Medical Imaging Systems ? X-ray Computed Tomography, Magnetic Resonanse Imaging. Brno: VUT in Brno, 2000. ISBN 80-214-1666-1.
[5] BUSHBERG, Jerrold T., J. Anthony SEIBERT, Edwin M. LEIDHOLDT a John M. BOONE. The essential physics of medical imaging. Third edition. Philadelphia: Wolters Kluwer Health/Lippincott Williams & Wilkins, 2012. ISBN 978-1-4511-1810-0.