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Contrast Enhancement in Images via the Product of Linear Filters
 Signal Processing
, 1999
"... An operator based on Products of Linear Filters is introduced in this Communication to perform image contrast enhancement. Translation invariance and isotropy conditions are derived. The proposed technique avoids noise amplification and is able to sharpen even small details. Keywords: Nonlinear ima ..."
Abstract

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An operator based on Products of Linear Filters is introduced in this Communication to perform image contrast enhancement. Translation invariance and isotropy conditions are derived. The proposed technique avoids noise amplification and is able to sharpen even small details. Keywords: Nonlinear image enhancement. 1 Introduction For the enhancement of the visual quality of an image, a Cubic Unsharp Masking (CUM) operator has been recently proposed [1]. This operator belongs to the wide family of the polynomial operators, which have already been employed in various applications in the digital signal processing area [2]. In the CUM technique the enhanced output is obtained by adding to the input signal a processed version of the signal itself, in which highfrequency components are nonlinearly amplified. Referring for simplicity to the 1D case, the output signal y n is obtained from the input x n through the relation y n = x n + z n ; (1) where is a positive factor used to control ...
The Frequency Domain Behavioral Modeling and Simulation of Nonlinear Analog Circuits and Systems
, 1993
"... LUNSFORD II, PHILIP J. The Frequency Domain Behavioral Modeling and Simulation of Nonlinear Analog Circuits and Systems. (Under the direction of Michael B. Steer.) A new technique for the frequencydomain behavioral modeling and simulation of nonautonomous nonlinear analog subsystems is presented. ..."
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LUNSFORD II, PHILIP J. The Frequency Domain Behavioral Modeling and Simulation of Nonlinear Analog Circuits and Systems. (Under the direction of Michael B. Steer.) A new technique for the frequencydomain behavioral modeling and simulation of nonautonomous nonlinear analog subsystems is presented. This technique extracts values of the Volterra nonlinear transfer functions and stores these values in binary files. Using these files, the modeled substem can be simulated for an arbitrary periodic input expressed as a finite sum of sines and cosines. Furthermore, the extraction can be based on any circuit simulator that is capable of steady state simulation. Thus a large system can be divided into smaller subsystems, each of which is characterized by circuit level simulations or lab measurements. The total system can then be simulated using the subsystem characterization stored as tables in binary files.