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Full Description
Digital image processing plays a crucial role in facilitating efficient storage, transmission, manipulation, and retrieval of images. Python, renowned for its open-source nature and strong community support, offers a user-friendly platform with extensive image processing capabilities through libraries such as computer vision and scikit-learn.
This textbook serves as a practical guide to digital image processing using Python, presenting fundamental concepts, techniques, and algorithms with illustrative examples in Python. Each chapter begins with clear learning objectives and concludes with exercises and multiple-choice questions for self-assessment. Drawing from a diverse range of sources including research articles and books, the references provided at the end of each chapter encourage further exploration.
Tailored for undergraduate and postgraduate students, research scholars, engineers, and faculty specializing in image processing, it assumes a foundational understanding of set theory, matrix algebra, probability, and random variables.
Contents
Chapter 1: elements of image processing.- Chapter 2: two dimensional convolution and correlaton.- Chapter 3: image transforms.- Chapter 4: image enhancement.- Chapter 5: image denoising and image restoration.- Chapter 6: morphological image processing.- Chapter 7: image segmentation.- Chapter 8: feature extraction.- Chapter 9: image compression.- Chapter 10: colour image processing.
