Paper
10 March 2010 Quadratic blur kernels for latent image formation modeling
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Abstract
A bilinear photoresist model is accurate, fast, and potentially reversible. Similar to other image-processing style (blur kernel) models, this model represents a transformation of an aerial image into a latent image. The key difference is the explicit recognition of the non-linearity of the process while retaining common signal processing architecture. By applying a Volterra series expansion to the reaction-diffusion functional, a high-accuracy representation of the process is obtained. Several methods for identifying the double-impulse response of the quadratic term of the series are discussed. Characterization is carried out based on the bi-harmonic signal sampling method of the Bilinear Transfer Function, the Fourier transform of the double-impulse spread function. Several photoresist systems are characterized, and strong quadratic behavior is observed for many. The resulting estimated BTF are presented, and their differences are discussed.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Anatoly Burov "Quadratic blur kernels for latent image formation modeling", Proc. SPIE 7640, Optical Microlithography XXIII, 76400P (10 March 2010); https://doi.org/10.1117/12.848295
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KEYWORDS
Photoresist materials

Spatial frequencies

Calibration

Image acquisition

Signal processing

Polymers

Fourier transforms

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