Feature-Oriented Signal Processing Under Nonlinear Partial Differential Equations

reportActive / Technical Report | Accession Number: ADA259951 | Open PDF

Abstract:

A successful nonlinear partial differential equation based approach to restoration was carried out, ENO least squares, shock filters, feature detectors and total variation based deconvolution techniques were combined. Also rigorous morphological methods and wavelet analysis were developed and used to restore noisy, blurry images.

Author(s):
Osher, Stanley ; Rudin, Leonid
Author Organization(s):
COGNITECH INC SANTA MONICA CA
Descriptive Note:
Final rept. 1 Nov 1989-31 Oct 1992
Supplementary Note:
DOI: 10.21236/ADA259951
Pagination:
0033

Security Markings

DOCUMENT & CONTEXTUAL SUMMARY

Distribution:
Approved For Public Release
Distribution Statement:
Approved For Public Release; Distribution Is Unlimited.

RECORD

Collection: TR
Identifying Numbers
Report Number(s):
AFOSR-TR-93-0023
Contract/Grant Number(s):
F49620-90-C-0011
Task Number(s):
A5
Project Number(s):
2304
Monitor Series:
TR-93-0023, AFOSR
 Subject Terms
Joint Capability Areas:
JCA_5_Command and Control; JCA_5.3_Planning; JCA_6.3.3_Spectrum Management; JCA_6_Net Centric; JCA_5.3.1_Analyze Problem; JCA_6.3_Net Management; JCA_1_Force Support
Modernization Areas:
Fully Networked C3
Communities of Interest:
Materials and Manufacturing Processes
Descriptor(s):
*SIGNAL PROCESSING, *NONLINEAR DIFFERENTIAL EQUATIONS, *APPLIED MATHEMATICS, DETECTORS, IMAGES, DIFFERENTIAL EQUATIONS, FILTERS, PARTIAL DIFFERENTIAL EQUATIONS, SHOCK, VARIATIONS
Field(s)/Group(s):
Numerical Mathematics, Cybernetics
Keyword(s):
PE61102F, WUAFOSR2304A5
Report Date:
1992 Jan 01