Results 1 
6 of
6
Adaptive, quadratic preprocessing of document images for binarization
, 1997
"... Abstract—This paper presents an adaptive algorithm for preprocessing document images prior to binarization in character recognition problems. Our method is similar in its approach to the blind adaptive equalization of binary communication channels. The adaptive filter utilizes a quadratic system mo ..."
Abstract

Cited by 6 (0 self)
 Add to MetaCart
(Show Context)
Abstract—This paper presents an adaptive algorithm for preprocessing document images prior to binarization in character recognition problems. Our method is similar in its approach to the blind adaptive equalization of binary communication channels. The adaptive filter utilizes a quadratic system model to provide edge enhancement for input images that have been corrupted by noise and other types of distortions during the scanning process. Experimental results demonstrating significant improvement in the quality of the binarized images over both direct binarization and a previously available preprocessing technique are also included in the paper. Index Terms—Blind equalization, character recognition, image preprocessing, nonlinear filtering. I.
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

Cited by 3 (1 self)
 Add to MetaCart
(Show Context)
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 ...
A running walshhadamard transform algorithm and its application to isotropic quadratic filter implementation
 in Proc. of EUSIPCO
, 1996
"... B b b b b b b b N N NN ..."
(Show Context)
DESIGN CONSTRAINTS FOR POLYNOMIAL AND RATIONAL FILTERS
"... Polynomial and rational filters for image enhancement, edge preserving noise smoothing, and interpolation of encoded images are usually designed as a weighted combination of nonlinear filters having lowpass or highpass behaviour. The choice of the filter components and of the coefficients is perform ..."
Abstract
 Add to MetaCart
(Show Context)
Polynomial and rational filters for image enhancement, edge preserving noise smoothing, and interpolation of encoded images are usually designed as a weighted combination of nonlinear filters having lowpass or highpass behaviour. The choice of the filter components and of the coefficients is performed heuristically, though. In this paper general design constraints for polynomial and rational filters are presented that are necessary to achieve isotropy, the preservation of the expectation value, and the detection of edges. For the application of edge preserving noise smoothing a method is derived to find an optimal polynomial or rational filter that meets these constraints. 1.
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. ..."
Abstract
 Add to MetaCart
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.