Digital Image Processing Color Models
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Digital Image Processing
A comprehensive digital image processing book that reflects new trends in this field such as document image compression and data compression standards. The book includes a complete rewrite of image data compression, a new chapter on image analysis, and a new section on image morphology.
Digital Image Processing
The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to: Applications and tools for image processing, and fundamentals with several implementation examples Concepts of image formation OpenCV installation with step-by-step screen shots Concepts behind intensity, brightness and contrast, color models Ways by which noises are created in an image and the possible remedial measures Edge detection, image segmentation, classification, regression, classification algorithms Importance of frequency domain in image processing field Relevant code snippets and the MATLAB® codes, and several interesting sets of simple programs in OpenCV and Python to aid learning and for complete understanding The video lectures for specific topics through YouTube enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quizzes and review questions fully prepare the readers for further study. Graduate students, post graduate students, researchers, and anyone in general interested in image processing, computer vision, machine learning domains etc. can find this book an excellent starting point for information and an able ally.
Fundamentals of Digital Image Processing
"Fundamentals of Digital Image Processing" is a comprehensive guide that delves into the intricacies of manipulating and analyzing digital images. We provide a thorough exploration of fundamental concepts, techniques, and applications in digital image processing. Catering to both beginners and seasoned professionals, the content spans a wide spectrum. Starting with the basics, we introduce core principles of digital image representation, pixel operations, and color models. We then progress into advanced topics such as image enhancement, filtering, and transformation, offering a deep understanding of the algorithms involved. The book covers image segmentation, a crucial aspect of image analysis, discussing various segmentation techniques and their applications in fields like medical imaging, computer vision, and pattern recognition. We also address the evolving field of image compression, highlighting methods to reduce image size without compromising essential information. One notable strength is our practical approach, integrating theory with hands-on examples and real-world applications. We equip readers with tools to implement image processing algorithms using popular programming languages and software. Case studies illustrate digital image processing's impact in diverse fields, including medicine, remote sensing, and multimedia. "Fundamentals of Digital Image Processing" is an indispensable resource for academics, researchers, and practitioners, offering theoretical knowledge and practical insights.