Publisher's Synopsis
Scientists routinely use MATLAB or Octave for computational applications, and still C/C++ or Fortran for more for rigorous modelling. However Python is gaining popularity in scientific computing, as it has built-in scientific support through packages and toolkits such as SciPy and NumPy. Being open-source it also has a strong community support developing packages and sharing expertise. Given this, it is inevitable that Python had become one of the most popular, flexible programming languages used today and it is finding applications in science and engineering for everything from basic scripting to machine learning; and signal processing is not immune to the march of Python.
This book explores the domain of image processing using Python, with the help of working examples and accompanying code. Aimed at researchers and advanced students with a knowledge of image processing fundamentals this book introduces the concepts of Python programming via image processing with numerous hands-on examples and code snippets. The book will enable readers to appreciate the power of Python in this field and write their own code and implement complex signal processing algorithms such as image enhancement, compression, restoration, segmentation, watermarking and encryption and be able to incorporate machine learning models using relevant Python libraries. The aim of this book is to bring together professionals from academia and industry to help readers develop their own applications, whether for software-based implementation or simulation and testing before a final hardware implementation, to present new developments and techniques in signal processing with Python or for applications in computer vision.
Key Features:
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Hands-on python examples and code for each chapter
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From basic to advanced topics
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Focus on practical applications
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Includes ML based applications
