UNIVERSITI PUTRA MALAYSIA

AFSANEH JALALIAN

FK 2010 67

CELLULAR AUTOMATON FOR EFFICIENT IMPULSE NOISE REMOVAL AND EDGE DETECTION USING

GRAPHIC PROCESSOR UNIT

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CELLULAR AUTOMATON FOR EFFICIENT IMPULSE NOISE REMOVAL AND EDGE DETECTION USING

GRAPHIC PROCESSOR UNIT

BY

AFSANEH JALALIAN

Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia, in Fulfilment of the Requirements for the Degree of Master

November 2010

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Dedicated

To:

This thesis dedicated to my beloved husband, Babak Karasfi, to my dear and

lovely daughter Parmida to my dear mother Tooba Soltanieh and my lovely father

Hossein Jalalian that I owe them all of success in my life

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Abstract of thesis presented to the Senate of Universiti Putra Malaysia, in fulfilment of the requirement for the degree of Master

ABSTRACT

CELLULAR AUTOMATON FOR EFFICIENT IMPULSE NOISE REMOVAL AND EDGE DETECTION USING GRAPHIC PROCESSOR

UNIT

BY

AFSANEH JALALIAN

November 2010

Chair: Khairulmizam b. Samsudin, PhD

Faculty: Engineering

Low cost sensors allow integration of image and video features in consumer

devices. Increasing image resolution and pixel dimension requires high

performance image processing technique preferably one that could be parallelize. In

the last few years, Graphics Processing Units have evolved into more flexible and

powerful data-parallel processors. Graphics Processing Units are economical and

are advantageous in a wide variety of computer architecture. Recent developments

in programmability and rapid growth in the performance of graphic hardware, has

provided groundwork for using the architecture in alternative domains of graphics

applications. In this respect, Cellular Automata could handle this requirement with

its parallel architecture. The characteristic of cellular automata is found to be highly

suitable for vector processor such as the Graphic Processor Unit and Field

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Programmable Gate Array. In recent years the tendency to use of cellular automata

in solving the problems of image processing has increased.

Noise removal and edge detection are fundamental operations, which commonly

applied as pre-processing step before subsequent image processing tasks. One of

the significant factors which degrade the performance of edge detector method is

noise.

This thesis present Cellular Automata models for noise removal and edge detection

of the distorted image by salt and pepper noise. In order to enhance the performance

of the Cellular Automata model, a Graphic Processor Units programming approach

has been adopted.

The results obtained show that the implemented Cellular Automata models are able

to suppress noise and edge extraction in high noise intensity to 90 percents. The

Cellular Automata models implemented on Graphic Processing Units have

successfully outperformed the method implemented on Central processing Unit by

factor of 2 for gray scale image and factor of 10 for colour images.

The results indicate that cellular automata executed on the Graphic Processor Units

build a solid foundation for the wide variety of application in image processing.

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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Master sainl

ABSTRAK

CELLUL AR AUTOMATON BAGI PENYINGKIRAN HINGAR DEDENYUT DAN PENGESANAN TEPI MENGGUNAKAN GRAPHIC

PROCESSOR UNIT

Oleh

AFSANEH JALALIAN

November 2010

Pengerusi: Khairulmizam b. Samsudin, PhD

Fakulti: Kejuruteraan

Penderia-penderia kos rendah membenarkan integrasi ciri-ciri imej dan video dalam

alat-alat pengguna. Peningkatan dimensi resolusi imej dan piksel memerlukan

teknik pemprosesan imej berprestasi tinggi yang sesuai serta bersiri. Dalam

beberapa tahun yang lalu, Graphics Processing Units telah berkembang maju

menjadi lebih fleksibel dan pemproses data-sesiri yang berkuasa. Graphics

Processing Units lebih ekonomik dan berfaedah untuk pelbagai jenis seni bina

komputer. Perkembangan terkini dalam pembangunan kebolehaturcaraan dan

pertumbuhan pesat dalam prestasi perkakasan grafik, telah menyediakan asas untuk

menggunakan seni bina ini dalam domain-domain alternatif bagi aplikasi grafik.

Sehubungan dengan itu, Cellular Automata boleh memenuhi syarat ini dengan seni

bina yang selari. Ciri-ciri Cellular Automata yang istimewa didapati amat sesuai

untuk pemproses vektor seperti Graphic Processor Unit dan Field Programmable

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Gate Array. Kebelakangan ini kecenderungan untuk penggunaan Cellular Automata

dalam menyelesaikan masalah-masalah pemprosesan imej telah meningkat.

Penyingkiran hingar dan pengesanan tebing adalah operasi yang asas, pada

kebiasaannya digunakan sebagai langkah pre- pemprosesan sebelum tugas-tugas

pemprosesan imej berikutnya. Salah satu faktor penting yang mengurangkan

prestasi kaedah pengesan pinggir ialah hingar.

Tesis ini mempersembahkan model Cellular Automata bagi penyingkiran bunyi

bising dan pengesanan pinggir imej terherot dengan hingar garam dan lada. Bagi

tujuan peningkatan prestasi, model Cellular Automata dibina dengan pendekatan

pengaturcaraan Graphic Processor Units.

Keputusan yang diperolehi menunjukkan pelaksanaan model Cellular Automata

berupaya mengurangkan hingar dan melaksanakan ekstraksi pinggir dalam

keamatan hingar peringkat tinggi hingga 90 peratus. Model Cellular Automata yang

dilaksanakan pada Graphic Processor Units telah berjaya mengungguli kaedah yang

diterapkan pada Central Processing Unit sebanyak 2 faktor untuk gambar skala

kelabu dan 10 faktor untuk gambar berwarna.

Keputusan menunjukkan Cellular Automata dilaksanakan pada Graphic Processor

Units dapat dijadikan sebuah asas yang kukuh kepada pelbagai jenis aplikasi yang

luas dalam pemprosesan imej.

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ACKNOWLEDGEMENTS

I thank Allah the almighty to have bestowed such consciousness and chance to

continue this endeavour onward.

I would like to express my deep gratefulness and gratitude for a lifetime to

Dr. Khairulmizam bin Samsudin for his wonderful advice, thoughtful guidance,

unceasing support and meaningful friendship throughout my Master degree. He

supported me through the difficulties and encouraged me to move to a higher level

of learning modern knowledge.

I would like to express my special appreciation and very sincere gratitude to the

member of my supervisory committee: Dr. M.Iqbal b. Saripan for scientific and

financial support through most of the duration of my PhD program. They gave me

the time, effort, encouragement and valuable suggestions.

I would like to thank Dr. Syamsiah bt. Mashohor for consistently supported my

interest to propose research questions and challenged me to answer them.

I would like to express my deep gratitude to my husband, Babak Karasfi for all

their assistance encouragement and support in letting me pursue my dreams.

Especially, I wish to thank my precious baby daughter, Parmida for opening up an

exciting world and bringing us joy and peace during the stages of my pursuing this

Master degree.

Afsaneh Jalalian

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APPROVAL

I certify that the a Thesis Examination Committee has been met on 4th of November, 2010 to conduct the final examination of Afsaneh Jalalian on her thesis entitled “Cellular Automaton for Efficient Impulse Noise Removal and Edge Detection using Graphic Processor Unit” in accordance with the Universities and University Collages Act 1971 and Constitution of the Universiti Putra Malaysia [P.U.(A) 106] 15 March 1998. The Committee recommended that the student be award the Master of Science degree. Member of Thesis Examination Committee were as follows:

Abdul Rahman bin Ramli, PhD Associate professor Faculty of Engineering University Putra Malaysia (Chairman) Makhfudzah binti Mokhtar, PhD Lecturer Faculty of Engineering University Putra Malaysia (Internal Examiner) Rahmita Wirza bt O.K. Rahmat, PhD Associate professor Faculty of Computer Science University Putra Malaysia (Internal Examiner)

Othman O. Khalifa, PhD Professor International Islamic University Malaysia (External Examiner)

BUJANG KIM HUAT, PhD Professor and Deputy Dean School of Graduate Studies Universiti Putra Malaysia

Date:

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APPROVAL

This thesis was submitted to the Senate of Universiti Putra Malaysia and has been accepted as fulfilment of the requirement for the degree of Master. The members of the Supervisory Committee were as follow: Khairulmizam b. Samsudin, PhD Lecturer Faculty of Engineering University Putra Malaysia (Chairman) M.Iqbal b. Saripan, PhD Lecturer Faculty of Engineering University Putra Malaysia (Member)

HASANAH MOHD GHAZALI, PhD

Professor and Dean School of Graduate Studies Universiti Putra Malaysia

Date:

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DECLARATION

I declare that the thesis is my original work except for quotations and citations which have been duly acknowledged. I also declared that it has not been previously, and is not concurrently, submitted for any other degree at Universiti Putra Malaysia or at any other institution.

AFSANEH JALALIAN

Date: 4 November 2010

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TABLE OF CONTENTS

Page 

ABSTRACT ii ABSTRAK iv ACKNOWLEDGEMENTS vi APPROVAL vii APPROVAL viii LIST OF TABLES xii LIST OF FIGURES xiii 

CHAPTER

1  INTRODUCTION 1 1.1  Thesis Overview 1 1.2  Problem Statement 2 1.3  Objectives 4 1.4  Contributions 5 1.5  Report Organization 5 

2  LITERATURE REVIEW 7 2.1  Introduction 7 2.2  Graphic Processor Units (GPU) 8 

2.2.1  Parallel Architecture of GPU 9 2.2.2  GPU Programming Language 13 2.2.3  Development Strategy 14 2.2.4  OpenGL API 19 2.2.5  Implementation with OpenGL Program 20 

2.3  The Fundamental of Image Processing Techniques 22 2.4  Image Noise 23 

2.4.1  Type of Noise 23 2.4.2  Image De-Noising 25 2.4.3  Evaluation Method 26 

2.5  Edge Detection 27 2.5.1  Gradient Based Edge Detector 27 2.5.2  Evaluation Method 29 

2.6  Cellular Automata (CA) 30 2.6.1  Preliminary Concept 31 2.6.2  CA Application in Image Processing 33 2.6.3  CA De-Noising Method 35 2.6.4  CA Edge Extractor 36 

2.7  Summary 39 

3  METHODOLOGY 40 3.1  Introduction 40 3.2  Cellular Automata Based Model over the GPU 41 

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3.2.1  GPU-Based CA Model for Noise Removal 41 3.2.2  GPU-Based CA Model for Edge Extraction of Noisy Image

43 3.3  Implementation of CPU-based CA Model for Noise Removal 45 

3.3.1  Bit-Mixing Median Filter 48 3.4  Implementation of CPU based CA Model for Edge Extraction of

Noisy Image 49 3.5  Test Images 51 3.6  Summary 54 

4  EXPERIMENTAL RESULT AND DISCUSSION 55 4.1  Introduction 55 4.2  Noise Removal 55 

4.2.1  Visual Assessment 55 4.2.2  Quantitative Assessment 66 4.2.3  Time Processing Assessment 70 

4.3  Edge Detection 72 4.3.1  Visual Assessment 73 4.3.2  Quantitative Assessment 77 4.3.1  Time Processing Assessment 82 

5  CONCLUSION 84 

REFERENCES 86 BIODATA OF STUDENT 92