• Title Digital Image Processing
• Author(s) Gholamreza Anbarjafari (Shahab)
• Publisher: University of Tartu
• Paperback N/A
• eBook HTML and Videos
• Language: English
• ISBN-10: N/A
• ISBN-13: N/A
• Share This:  

Book Description

This e-course is designed to give the people who are interested in image processing the fundamental concepts in digital image processing with emphasis in sampling, quantization, interpolation, filtering, and spatial domain enhancement. At the end of this e-course, students will learn the signal processing algorithms and techniques in image enhancement. They will be able to conduct independent study and analysis of image processing problems and techniques.

It introduces the fundamental concepts of modern digital image processing. It aims to help the students, scientists, and practitioners to understand the concepts through clear explanations, illustrations and examples.

It covers two-dimensional (2D) and three-dimensional (3D) imaging techniques, image printing and storage methods, image processing algorithms, image and feature measurement, quantitative image measurement analysis, and more.

• Dr. Gholamreza Anbarjafari is an Assoc. Professor of Image Processing in IMS Lab at University of Tartu.

• Amazon

• Digital Signal Processing (DSP), Sound and Imaging Processing
• Computer and Machine Vision
• Computer Graphics, 3D, Animation and Imaging
• Electronic Engineering

• Digital Image Processing (Gholamreza Anbarjafari)
• The Mirror Site (1) - PDF
• The Mirror Site (2) - PDF

• Plenoptic Imaging and Processing (Lu Fang)

  This open access book delves into the fundamental principles and cutting-edge techniques of plenoptic imaging and processing. Plenoptic imaging aims to detect and reconstruct multidimensional and multiscale information from light rays in space.

• Image Processing in C, 2nd Edition (Dwayne Philipps)

  This book is a tutorial on image processing. Each chapter explains basic concepts with words and figures, shows image processing results with photographs, and implements the operations in C.

• Genetic and Evolutionary Computation for Image Processing

  Image analysis and processing is steadily gaining relevance within the large number of application fields to which genetic and evolutionary computation (GEC) techniques are applied. This book is the first attempt to offer a panoramic view on the field.

• Principles of Computerized Tomographic Imaging (Avinash C. Kak)

  A comprehensive, tutorial-style introduction to the algorithms for reconstructing cross-sectional images from projection data and contains a complete overview of the engineering and signal processing algorithms necessary for tomographic imaging.

• Natural Image Statistics in Digital Image Forensics (Siwei Lyu)

  This book provides the first general framework, based on universal statistical properties of natural images, of detecting tampering and authenticating digital images that has been successfully applied to three problems in digital image forensics.

• Natural Image Statistics: A Probabilistic Approach (A. Hyvarinen)

  This book is both an introductory textbook and a research monograph on modelling the statistical structure of natural images. The statistical structure is described using a number of statistical models whose parameters are estimated from image samples.

• Introduction to Programming for Image Analysis with VTK

  Provide sufficient introductory material for engineering graduate students with background in programming in C and C++ to acquire the skills to leverage modern open source toolkits in medical image analysis and visualization.

• Handbook of Digital Face Manipulation and Detection

  This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the both biometrics and media forensics fields.

• Computer Vision: Algorithms and Applications, Second Edition

  This book explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications as well as for fun, consumer-level tasks.