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Digital Image Processing using MATLAB : ZERO to HERO

by arsathnatheem
Download PDF of Digital Image Processing using MATLAB: ZERO to HERO Practical Approach with Source Code (Handbook of Digital Image Processing using MATLAB 1) by Arsath Natheem

Book Description

This book will teach you everything you need to know about digital image processing. The significance and requirement of image processing derives from two application areas: the enhancement of data for human interpretation and the processing of spectacle data for machine perception. Digital image processing is used in a wide variety of applications, including remote sensing, picture and data storage for transmission in acoustic imaging, medical imaging, corporate applications, forensic sciences, and industrial automation. Images aid in the tracking and forecasting of earth resources, urban populations, agricultural crops, climate forecasts, flooding, and fire management. The applications of space imaging include the comprehension and analysis of objects contained in photographs acquired by deep space probe missions. Additionally, there are medical programmes such as X-ray processing, ultrasound scanning, electron microscopy, magnetic resonance imaging, and nuclear magnetic resonance imaging. Apart from the aforementioned applications, digital image processing is utilised to address a wide variety of problems. Even if unrelated, these issues frequently need the use of information-improvement techniques. Processing of images Procedures including as restoration and image enhancement are used to restore deteriorated or fuzzy images. There are several applications of image processing techniques in military, astronomy, biology, medicine, and industry. As far as Medical Imaging is concerned, practically all of the images can be used to detect cancers or to view patients. At the moment, the primary application of digital image processing (DIP) approaches is in resolving machine vision problems in order to achieve superior results.
 
BOOK INTRO VIDEO

CONTENTS OF THIS BOOK:

Chapter 1: MATLAB Source Code for Basic Morphological Operations
Chapter 2: Image Segmentation Using MATLAB
Chapter 3: MATLAB Source Code for Image Intensity Transformation
Chapter 4: Equalization of Histograms with MATLAB Source Code
Chapter 5: Resolving Spatial Intensity with MATLAB Source Code
Chapter 6: MATLAB Source Code for Image Enhancement in Frequency Filtering
Chapter 7: MATLAB Source Code for Image Enhancement in Spatial Filtering
Chapter 8: MATLAB Source Code for Color Image Processing
Chapter 9: DFT Analysis Using MATLAB
Chapter 10: MATLAB Source Code for the Basic Thresholding Function
Chapter 11: MATLAB Source Code for Image Sampling and Quantization
Chapter 12: MATLAB Source Code for Various Image Transformations
 
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