Applied Digital Imaging

Book Series: Image Processing for Embedded Devices

Volume 1

by

Sebastiano Battiato, Arcangelo Ranieri Bruna, Giuseppe Messina, Giovanni Puglisi

DOI: 10.2174/97816080517001100101
eISBN: 978-1-60805-170-0, 2010
ISBN: 978-1-60805-560-9
ISSN: 1879-7458

  
  




Embedded imaging devices such as digital still and video cameras, mobile phones, personal digital assistants, and visual sensors for s...[view complete introduction]
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Table of Contents

Foreword , Pp. i

Francisco Imai
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Preface , Pp. ii-iii (2)

Sebastiano Battiato, Arcangelo Ranieri Bruna, Giuseppe Messina and Giovanni Puglisi
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Biographies , Pp. iv-vi (3)

Sebastiano Battiato
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List of Contributors , Pp. vii

Sebastiano Battiato, Arcangelo Ranieri Bruna, Giuseppe Messina and Giovanni Puglisi
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Acknowledgements , Pp. viii

Sebastiano Battiato, Arcangelo Ranieri Bruna, Giuseppe Messina and Giovanni Puglisi
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Fundamentals and HW/SW Partitioning , Pp. 1-9 (9)

S. Battiato, G. Puglisi, A. Bruna, A. Capra and M. Guarnera
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Notions about Optics and Sensors , Pp. 10-33 (24)

A. Bruna, A. Capra, M. Guarnera and G. Messina
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Exposure Correction , Pp. 34-53 (20)

A. Castorina and G. Messina
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Pre-acquisition: Auto-focus , Pp. 54-91 (38)

A. Capra and S. Curti
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Color Rendition , Pp. 92-116 (25)

A. Bruna and F. Naccari
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Noise Reduction , Pp. 117-148 (32)

A. Bosco and R. Rizzo
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Demosaicing and Aliasing Correction , Pp. 149-190 (42)

M. Guarnera, G. Messina and V. Tomaselli
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Red Eyes Removal , Pp. 191-216 (26)

G. Messina and T. Meccio
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Video Stabilization , Pp. 217-236 (20)

T. Meccio, G. Puglisi and G. Spampinato
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Image Categorization , Pp. 237-269 (33)

G. M. Farinella and D. Ravi
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Image and Video Coding and Formatting , Pp. 270-309 (40)

A. Bruna, A. Buemi and G. Spampinato
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Quality Metrics , Pp. 310-342 (33)

Ivana Guarneri
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Beyond Embedded Device , Pp. 343-373 (31)

S. Battiato, A. Castorina and G. Messina
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Index , Pp. 374-376 (3)

Sebastiano Battiato, Arcangelo Ranieri Bruna, Giuseppe Messina and Giovanni Puglisi
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Foreword

Image Processing in embedded devices has been an area of growing interest with the revolution of digital imaging devices since the last decade of the 20th century and it will continue to expand to new frontiers in this century. Despite its relevance, there is not, as far as I know, a comprehensive publication that address this topic encompassing practical aspects of image processing design.

With chapters contributed by both experienced researchers from academia as well as researchers and engineers from industry, the present publication covers fundamental aspects of image processing in embedded devices such as exposure correction, auto-focus, color rendition, noise reduction, demosaicing, encoding, red-eye removal, image categorization and presents relevant quality metrics and also recent trends in imaging.

The editors have done an excellent job of bringing out contributors that work with the challenges of finding solutions and also implementing image processing solutions for embedded imaging devices in a daily basis with continuous spread across all relevant operational aspects for an imaging system.

I believe, the present publication is going to be beneficial not only to imaging and engineering students but also be a reference for academic researchers and engineers working in imaging industry.

This publication is also unique because it moves away form the traditional paper book for technical publications and follows the trend of electronic book. This makes the publication more accessible, more portable with current e-readers in the market, potentially more environment friendly without ever going out of print. Electronic publications also attribute such language accessibility by electronic translations and text-to-speech software capabilities.

It is a great pleasure for me to write a foreword for this prestigious, multi-authored, international publication on a topic that I believe is very relevant to the imaging industry. Finally, I would like to compliment the editors and contributors for their effort in making this publication a great success.

Francisco Imai, Ph.D.
Principal Scientist
Canon Development Americas, Inc.
3300 North First Street
San Jose, CA, 95134 USA


Preface

Embedded imaging devices, such as digital still and video cameras, mobile phones, personal digital assistants, and visual sensors for surveillance and automotive applications, make use of the single-sensor technology approach. An electronic sensor (Charge Coupled Device - CCD or Complementary Metal-Oxide-Semiconductor - CMOS) is used to acquire the spatial variations in light intensity and then uses image processing algorithms to reconstruct a color picture from the data provided by the sensor. Acquisition of color images requires the presence of different sensors for different color channels. Manufacturers reduce the cost and complexity by placing a color filter array (CFA) on top of a single sensor, which is basically a monochromatic device, to acquire color information of the true visual scene.

The overall performance of any device are the result of a mixture of different components including hardware and software capabilities and, not ultimately, overall design (i.e., shape, weight, style, etc.).

This book is devoted to cover algorithms and methods for the processing of digital images acquired by single-sensor imaging devices. Typical imaging pipelines implemented in single-sensor cameras are usually designed to find a trade-off between sub-optimal solutions (devoted to solve imaging acquisition) and technological problems (e.g., color balancing, thermal noise, etc.) in a context of limited hardware resources. State of the art techniques to process multichannel pictures, obtained through color interpolation from CFA are very advanced. On the other hand, not too much is known and published about the application of image processing techniques directly on CFA images, i.e. before the color interpolation phase.

The various chapters of the book cover all aspects of algorithms and methods for the processing of digital images acquired by imaging consumer devices. More specifically, we will introduce the fundamental basis of specific processing into CFA domain (demosaicing, enhancement, denoising, compression). Also ad-hoc matrixing and color balancing techniques devoted to preprocess input data coming from the sensor will be treated. In almost all cases various arguments have been presented in a tutorial way in order to provide to the readers a comprehensive overview of the main basis of each involved topics. All contributors are well renowned experts in the field as demonstrated by the number of related patents and scientific publications.

The main part of the book analyzes the various aspects of the imaging pipeline from the CFA data to image and video coding. A typical imaging pipeline is composed by two functional modules (pre-acquisition and post-acquisition) where the data coming from the sensor in the CFA format are properly processed. The term pre-acquisition is referred to the stage in which the current input data coming from the sensor are analyzed just to collect statistics useful to set parameters for correct acquisition.

The book also contains a number of chapters that provide solution and methods to address some undesired drawbacks of acquired images (e.g., red-eye, jerkiness, etc.); an overview of the current technologies to measure the quality of an image is also given. Just considering the impressive (and fast) growth in terms of innovation and available technology we conclude the book just presenting some example of solution that makes ii use of machine learning for image categorization and a brief overview of recent trends and evolution in the field.

Catania (Italy), June 2010.

Sebastiano Battiato
Arcangelo Ranieri Bruna
Giuseppe Messina
Giovanni Puglisi

List of Contributors

Editor(s):
Sebastiano Battiato
University of Catania
Italy


Arcangelo Ranieri Bruna
University of Catania
Italy


Giuseppe Messina
University of Catania
Italy


Giovanni Puglisi
University of Catania
Italy




Contributor(s):
Sebastiano Battiato
Image Processing Lab
University of Catania
Italy


Giovanni Maria Farinella
Image Processing Lab
University of Catania
Italy


Tony Meccio
Image Processing Lab
University of Catania
Italy


Giovanni Puglisi
Image Processing Lab
University of Catania
Italy


Rosetta Rizzo
Image Processing Lab
University of Catania
Italy


Angelo Bosco
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Arcangelo Ranieri Bruna
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Antonio Buemi
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Alessandro Capra
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Alfio Castorina
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Salvatore Curti
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Mirko Guarnera
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Ivana Guarneri
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Giuseppe Messina
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Filippo Naccari
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Daniele Ravi‘
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Giuseppe Spampinato
Advanced System Technology - Catania Lab
STMicroelectronics
Italy


Valeria Tomaselli
Advanced System Technology - Catania Lab
STMicroelectronics
Italy




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