2D-discontinuity detection from scattered data
type: Item
instance of: scholarly article
title: 2D-discontinuity detection from scattered data
zbMATH Open document ID: 0916.65009
DOI: 10.1007/BF02684351
author: K. Appert
published in: Computing
publication date: 1999-07-06T00:00:00Z
review text: The paper describes a numerical approach for the detection of discontinuities of a 2D function distorted by noise. The proposed method is based on the 2D continuous wavelet transform and follows some previously obtained results of the author. Section 2 introduces the 2D wavelet transform, defines the wavelet transform modulus maxima, and gives a characterization of the wavelet transform behaviour in the neighbourhood of a maximum corresponding to a function value discontinuity. Section 3 performs a statistical test to detect the discontinuity curve in the presence of noise. Section 4 provides a detection algorithm from scattered and noisy data. This kind of problems arises in many applications within computer vision, geology, signal processing, etc. Section 5 contains numerical results supporting the proposed approach.
reviewed by: Neculai Curteanu
Mathematics Subject Classification ID: 65D15
Mathematics Subject Classification ID: 65T40
Mathematics Subject Classification ID: 60G35
Mathematics Subject Classification ID: 65C99
Mathematics Subject Classification ID: 93E10
Mathematics Subject Classification ID: 68U05
zbMATH DE Number: 1233903
zbMATH Keywords: 2D-discontinuity detection
zbMATH Keywords: edge-detection
zbMATH Keywords: numerical examples
zbMATH Keywords: continuous wavelet transform
zbMATH Keywords: detection algorithm
zbMATH Keywords: scattered and noisy data
zbMATH Keywords: computer vision
zbMATH Keywords: signal processing
MaRDI profile type: Publication
cites work: Q4325837
cites work: The wavelet transform, time-frequency localization and signal analysis
cites work: Smooth interpolation of large sets of scattered data
cites work: Singularity detection and processing with wavelets
cites work: Irregularity detection from noisy data in one and two dimensions
description: scientific article; zbMATH DE number 1233903