wavelet-based outlier detection and denoising of airborne laser scanning data a thesis submitted ...

129 Pages·2008·5.61 MB·English

WAVELET-BASED OUTLIER DETECTION AND DENOISING
OF AIRBORNE LASER SCANNING DATA

A THESIS SUBMITTED TO
GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
OF
MIDDLE EAST TECHNICAL UNIVERSITY

BY

TOLGA AKYAY

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR
THE DEGREE OF MASTER OF SCIENCE
IN
GEODETIC AND GEOGRAPHICAL INFORMATION TECHNOLOGIES

DECEMBER 2008
Approval of thesis:

WAVELET-BASED OUTLIER DETECTION AND DENOISING
OF AIRBORNE LASER SCANNER DATA

submitted by TOLGA AKYAY in partial fulfillment of the requirements for the degree of
Master of Science in Geodetic and Geographical Information Technologies
Department, Middle East Technical University by,

Prof. Dr. Canan Özgen
Dean, Graduate School of Natural and Applied Sciences

Assoc. Prof. Dr. H. Şebnem Düzgün
Head of Department,
Geodetic and Geographical Information Technologies

Assoc. Prof. Dr. Mahmut Onur Karslıoğlu
Supervisor, Civil Engineering Dept., METU

Examining Committee Members:

Prof. Dr. Vedat Toprak
Geological Engineering Dept., METU

Assoc. Prof. Dr. Mahmut Onur Karslıoğlu
Civil Engineering Dept., METU

Prof. Dr. Kerim Demirbaş
Electrical and Electronics Engineering Dept., METU

Dr. Engin Karaesmen
Civil Engineering Dept., METU

Dr. Uğur Murat Leloğlu
TÜBİTAK-UZAY

Date: 01/12/2008
I hereby declare that all information in this document has been
obtained and presented in accordance with academic rules and
ethical conduct. I also declare that, as required by these rules and
conduct, I have fully cited and referenced all material and results
that are not original to this work.

Name, Last name : Tolga AKYAY

Signature :
iii
ABSTRACT

WAVELET-BASED OUTLIER DETECTION AND DENOISING
OF AIRBORNE LASER SCANNING DATA

AKYAY, Tolga
M.Sc., Department of Geodetic and Geographic Information Technologies
Supervisor: Assoc. Prof. Dr. Mahmut Onur KARSLIOĞLU

December 2008, 115 pages

The method of airborne laser scanning – also named as LIDAR – has recently
turned out to be an efficient way for generating high quality digital surface
and elevation models. In this work, wavelet-based outlier detection and
different wavelet thresholding (wavelet shrinkage) methods for denoising of
airborne laser scanning data are discussed. The task is to investigate the
effect of wavelet-based outlier detection and find out which wavelet
thresholding methods provide best denoising results for post-processing.
Data and results are analyzed and visualized by using a MATLAB program
which was developed during this work.

Keywords: Outlier detection, wavelet thresholding, image denoising, LIDAR,
DEM
iv
ÖZ

HAVADAN LAZER TARAMA VERİSİNDE DALGACIK TABANLI
AYKIRI DEĞER BELİRLEME VE GÜRÜLTÜ TEMİZLEME

AKYAY, Tolga
Yüksek Lisans, Jeodezi ve Coğrafi Bilgi Teknolojileri Bölümü
Tez Yöneticisi: Doç. Dr. Mahmut Onur KARSLIOĞLU

Aralık 2008, 115 Sayfa

Havadan lazer tarama veya LIDAR olarak da adlandırılan yöntem son yıllarda
yüksek kalitede sayısal yüzey ve yükseklik modeli oluşturmada hızlı ve verimli
olmuştur. Bu çalışmada, havadan lazer tarama verisinde dalgacık tabanlı
aykırı değerlerin belirlenmesi ve değişik dalgacık sıkıştırma yöntemleri
kullanılarak havadan lazer tarama verisinde gürültü temizlenmesi tartışılmıştır.
Amaç, ileri aşamalardaki çalışmalarda fayda sağlaması için dalgacık tabanlı
aykırı değer belirlemenin etkisini araştırmak ve hangi dalgacık sıkıştırma
yönteminin gürültü temizlenmesinde daha iyi sonuçlar verdiğini bulmaktır.
Veri ve sonuçlar bu çalışmada geliştirilen bir MATLAB uygulaması tarafından
analiz edilmiş ve görüntülenmiştir.

Anahtar kelimeler: Aykırı değer belirleme, dalgacık sıkıştırma, görüntülerde
gürültü temizleme, LIDAR, DEM
v
ACKNOWLEDGEMENTS

I would like to express my sincere gratitude to Assoc. Prof. Dr. Mahmut Onur
Karslıoğlu for being a mentor in this field of study and guiding me throughout
my research.

I am also grateful to my family for supporting me throughout my educational
life.

I would also like to thank MNG Bilgisayar A.Ş. family for their support,
understanding and motivation.
vi
TABLE OF CONTENTS

ABSTRACT............................................................................iv
ÖZ.........................................................................................v
ACKNOWLEDGEMENTS.........................................................vi
TABLE OF CONTENTS...........................................................vii
LIST OF TABLES ................................................................... x
LIST OF FIGURES...............................................................xiv
CHAPTER
1 INTRODUCTION ................................................................ 1
2 LIDAR ............................................................................... 4
2.1 General Description..........................................................4
2.2 System Components........................................................5
2.3 Products.........................................................................8
3 DIGITAL ELEVATION MODEL............................................. 9
3.1 General Description..........................................................9
3.2 Production....................................................................10
3.3 Uses ............................................................................12
4 IMAGE DENOISING USING WAVELETS ............................ 13
4.1 Introduction..................................................................13
4.2 Wavelet Domain Filtering................................................16
vii
4.3 Discrete Wavelet Transform............................................16
4.4 Wavelet-Based Denoising ...............................................18
4.4.1 VisuShrink...............................................................21
4.4.2 NormalShrink ..........................................................22
4.4.3 SureShrink..............................................................22
4.4.4 BayesShrink............................................................23
4.4.5 Hypothesis Testing...................................................24
4.4.6 Generalized Cross-validation......................................27
4.5 Wavelet-Based Outlier Detection .....................................29
5 PROGRESSIVE MORPHOLOGICAL FILTERING.................. 31
5.1 Introduction..................................................................31
5.2 Morphological Filters ......................................................32
5.3 Progressive Morphological Filter.......................................33
5.4 Parameters for Progressive Morphological Filter.................35
6 TEST DATA...................................................................... 38
7 METHODOLOGY............................................................... 42
7.1 Introduction..................................................................42
7.2 Wavelet-Based Outlier Detection .....................................43
7.3 Interpolation.................................................................44
7.4 Wavelet-Based Denoising ...............................................45
7.5 Progressive Morphological Filtering ..................................46
8 RESULTS AND DISCUSSION............................................. 48
8.1 Introduction..................................................................48
8.2 Wavelet-Based Outlier Detection .....................................48
8.2 Wavelet-Based Denoising ...............................................50
viii
9 CONCLUSIONS ................................................................ 58
REFERENCES...................................................................... 60
APPENDICIES
A TEST RESULTS................................................................. 65
B KEY FUNCTIONS USED AND IMPLEMENTED IN MATLAB 114
C IMPLEMENTED WAVELET MODELS................................. 115

ix
LIST OF TABLES

Table 6.1: Summary of sites...............................................................................................39
Table 6.2: City sites............................................................................................................40
Table 6.3: Forest sites........................................................................................................41
Table 7.1: Progressive morphological filter parameters.......................................................47
Table 8.1: Summary of wavelet-based denoising results for DSM generation......................51
Table 8.2: Summary of wavelet-based denoising results for DEM generation......................51
Table 8.3: Overall denoising performance analysis for DSM generation on City Site 4 including
outliers...................................................................................................................52
Table 8.4: Overall denoising performance analysis for DSM generation on City Site 4
excluding outliers...................................................................................................52
Table 8.5: Overall denoising performance analysis for DEM generation on City Site 3 including
outliers...................................................................................................................56
Table 8.6: Overall denoising performance analysis for DEM generation on City Site 3
excluding outliers...................................................................................................56
Table A.1: Results of outlier detection for DSM generation..................................................65
Table A.2: Results of outlier detection for DEM generation..................................................65
Table A.3: Results of VisuShrink with hard thresholding for DSM generation on City Site 1
including outliers....................................................................................................66
Table A.4: Results of VisuShrink with hard thresholding for DEM generation on City Site 1
including outliers....................................................................................................67
Table A.5: Results of VisuShrink with hard thresholding for DSM generation on City Site 1
excluding outliers...................................................................................................68
Table A.6: Results of VisuShrink with hard thresholding for DEM generation on City Site 1
excluding outliers...................................................................................................69
Table A.7: Results of VisuShrink with soft thresholding for DSM generation on City Site 1
including outliers....................................................................................................70
Table A.8: Results of VisuShrink with soft thresholding for DEM generation on City Site 1
including outliers....................................................................................................71
x