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Digital image processing = illustration using Python /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Digital image processing/ by S Esakkirajan, T Veerakumar, Badri Narayan Subudhi.
Reminder of title:	illustration using Python /
Author:	Esakkirajan, S.
other author:	Veerakumar, T.
Published:	Singapore :Springer Nature Singapore : : 2025.,
Description:	xxiv, 870 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
Subject:	Image processing - Digital techniques. -
Online resource:	https://doi.org/10.1007/978-981-96-6382-8
ISBN:	9789819663828

Digital image processing = illustration using Python /
Esakkirajan, S.

Digital image processingillustration using Python /[electronic resource] :by S Esakkirajan, T Veerakumar, Badri Narayan Subudhi. - Singapore :Springer Nature Singapore :2025. - xxiv, 870 p. :ill. (some col.), digital ;24 cm.

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.

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.

ISBN: 9789819663828

Standard No.: 10.1007/978-981-96-6382-8doiSubjects--Topical Terms:

555959
Image processing
--Digital techniques.

LC Class. No.: TA1637

Dewey Class. No.: 621.367

Digital image processing = illustration using Python /
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