Image Operators : Image Processing in Python

For decades, researchers have been developing algorithms to manipulate and analyze images. From this, a common set of image tools now appear in many high-level programming languages. Consequently, the amount of coding required by a user has significantly lessened over the years. While the libraries for image analysis are coalescing to a common toolkit, the language of image analysis has remained stagnant. Often, textual descriptions of an analytical protocol consume far more real estate than does the computer code required to execute the processes. Furthermore, the textual explanations are sometimes vague or incomplete. This book offers a precise mathematical language for the field of image processing. Defined operators correspond directly to standard library routines, greatly facilitating the translation between mathematical descriptions and computer script. This text is presented with Python 3 examples. • This text will provide a unified language for image processing • Provides the theoretical foundations with accompanied Python scripts to precisely describe steps in image processing applications • Linkage between scripts and theory through operators will be presented • All chapters will contain theories, operator equivalents, examples, Python codes, and exercises Part I - Image Operators -- Operator Nomenclature -- Scripting in Python -- Digital Images -- Color -- Part II Image Space Manipulations -- Geometric Transformations -- Image Morphing -- Principle Component Analysis -- Eigenimages -- Part III Frequency Space Manipulations -- Image Frequencies -- Filtering in Frequency Space -- Correlations -- Part IV Texture and Shape -- Edge Detection -- Hough Transforms -- Noise -- Texture Recognition -- Gabor Filtering -- Describing Shape -- Part V Basis -- Basis Sets -- Pulse Images and Autowaves This book will provide a unified theoretical foundation of image analysis procedures with accompanied Python computer scripts to precisely describe the steps in image processing applications. Linkage between required scripts and theory through operators will be presented. Readers will be able to quickly write computer code to correctly implement the algorithms. Chapters will contain theories, operator equivalents, examples, Python codes, and exercises. Python downloads will be available Read more... Abstract: "A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc." Read more... "Sixty years after its birth, Synthetic aperture radar (SAR) evolved as a key player of earth observation, and it is continually upgraded by enhanced hardware functionality and improved overall performance in response to user requirements. The basic information gained by SAR includes the backscattering coefficient of targets, their phases (the truncated distance between SAR and its targets), and their polarization dependence. The spatiotemporal combination of the multiple data operated on the satellite or aircraft significantly increases its sensitivity to detect changes on earth, including temporal variations of the planet in amplitude and the interferometric change for monitoring disasters; deformations caused by earthquakes, volcanic activity, and landslides; environmental changes; ship detection; and so on. Earth-orbiting satellites with the appropriate sensors can detect environmental changes because of their large spatial coverage and availability. Imaging from spaceborne and airborne SARs, calibration, and applications provides A-to-Z information regarding SAR researches through 15 chapters that focus on the JAXA L-band SAR. Sample data are created by using L-band SAR, JERS-1, PALSAR, PALSAR-2, and Pi-SAR-L2." Content: PART I Image Operators. 1 Introduction. 2 Operator Nomenclature. 3 Scripting in Python. 4 Digital Images. 5 Color. PART II Image Space Manipulations. 6 Geometric Transformations. 7 Image Morphing. 8 Principle Component Analysis. 9 Eigenimages. PART III Frequency Space Manupulations. 10 Image Frequemncies. 11 Filtering in Frequency Space. 12 Correlations. PART IV Texture and Shape. 13 Edge Detection. 14 Hough Transforms. 15 Noise. 16 Texture Recognition. 17 Gabor Filtering. 18 Describing Shape. PART V Basis. 19 Basis Sets. 20 Pulse Images and Autowaves. Appendix A Operators. Appendix B Operators in Symbolic Order. Appendix C Lengthy Codes. Bibliography. Introduction -- Introduction of the SAR system -- SAR imaging and analysis -- Radar equation for SAR correlation power : radiometry -- Scansar imaging -- Polarimetric calibration model as a radiometry -- SAR elevation antenna pattern : theory and measured pattern from the natural target data -- Geometry/ortho-rectification and slope-corrections -- Calibration-radiometry and geometry -- Defocusing and image shift due to the moving target -- Mosaicking and multi-temporal SAR imaging -- SAR interferometry -- Irregularities (RFI and ionosphere) -- Applications -- Forest map generation This book will provide a unified theoretical foundation of image analysis procedures with accompanied Python computer scripts to precisely describe the steps in image processing applications. Linkage between required scripts and theory through operators will be presented. Readers will be able to quickly write computer code to correctly implement the algorithms. Chapters will contain theories, operator equivalents, examples, Python codes, and exercises. Python downloads will be available-- Provided by publisher This book will provide a unified theoretical foundation of image analysis procedures with accompanied Python (R) computer scripts to precisely describe the steps in image processing applications. Linkage between required scripts and theory through operators will be presented.