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Smart Image Processing in Modern Communication Systems is a comprehensive textbook that presents the fundamental concepts, techniques, and applications of digital image processing with a strong emphasis on modern communication systems. Designed for undergraduate and postgraduate students in Electronics and Communication Engineering, Computer Science, Information Technology, Artificial Intelligence, and related disciplines, the book bridges theoretical foundations with practical applications.
The book begins with the fundamentals of digital images, including image representation, sampling, quantization, pixel relationships, and image transforms such as FFT, Walsh, Hadamard, DCT, and DWT. It then explores image enhancement techniques in both spatial and frequency domains, covering gray-level transformations, histogram processing, filtering methods, and image sharpening.
Subsequent chapters focus on image restoration, addressing degradation models, noise reduction, inverse filtering, Wiener filtering, and constrained least squares restoration techniques. The book further introduces image segmentation through thresholding, edge-based, region-based, and morphological approaches, enabling readers to understand object detection and image analysis.
The final chapter discusses image compression, including lossless and lossy compression techniques, predictive encoding, coding models, compression standards, and JPEG implementation, providing readers with essential knowledge for efficient image storage and transmission.
Featuring well-structured explanations, illustrations, mathematical concepts, and practical examples, this book serves as an ideal resource for students, researchers, academicians, and professionals seeking a solid understanding of image processing technologies and their applications in contemporary communication systems.
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