Hybrid and Advanced Compression Techniques for Medical Images (PDF)
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This book introduces advanced and hybrid compression techniques specifically used for medical images. The book discusses conventional compression and compressive sensing (CS) theory based approaches that are designed and implemented using various image transforms, such as: Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Singular Value Decomposition (SVD) and greedy based recovery algorithm. The authors show how these techniques provide simulation results of various compression techniques for different types of medical images, such as MRI, CT, US, and x-ray images. Future research directions are provided for medical imaging science. The book will be a welcomed reference for engineers, clinicians, and research students working with medical image compression in the biomedical imaging field.
- Covers various algorithms for data compression and medical image compression;
- Provides simulation results of compression algorithms for different types of medical images;
- Provides study of compressive sensing theory for compression of medical images.
Dr. Ashish M. Kothari obtained his Ph.D. in Digital Video Watermarking from JJT University, Rajasthan, India. He is an Associate professor and Head of Electronics and Communication Engineering at Atmiya Institute of Technology and Science, Rajkot, Gujarat, India. He is also a recognized Ph.D. supervisor at Gujarat Technological University, Ahmedabad. His primary areas of research are Image Processing, Video Processing, Digital Watermarking, and Signal Processing. He has published one book and more than 25 research papers in refereed and indexed journals and conferences at the international and national level.
- Autoren: Rohit M. Thanki , Ashish Kothari
- 2019, 1st ed. 2019, 95 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3030125750
- ISBN-13: 9783030125752
- Erscheinungsdatum: 22.02.2019
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 3.84 MB
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