Digital Image Processing By Jayaraman S, Veerakumar T, Esakkirajan S

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Digital Image Processing: A Pragmatic Approach by Jayaraman, Veerakumar and Esakkirajan
Digital image processing is the field of study that deals with manipulating and analyzing images using various techniques and algorithms. It has applications in many domains such as computer vision, medical imaging, biometrics, remote sensing, security, entertainment and more.
One of the most popular and comprehensive books on digital image processing is Digital Image Processing by S. Jayaraman, T. Veerakumar and S. Esakkirajan. This book provides a clear, up-to-date and practical introduction to the subject for students and practicing engineers. It covers the fundamental concepts and methods of image processing such as image representation, enhancement, restoration, segmentation, compression, feature extraction, recognition and classification. It also includes illustrative examples and MATLAB applications to help readers understand and implement the theory in practice.
The book is divided into 12 chapters that cover the following topics:

Chapter 1: Introduction to Digital Image Processing
Chapter 2: Digital Image Fundamentals
Chapter 3: Image Enhancement in Spatial Domain
Chapter 4: Image Enhancement in Frequency Domain
Chapter 5: Image Restoration
Chapter 6: Color Image Processing
Chapter 7: Image Compression
Chapter 8: Morphological Image Processing
Chapter 9: Image Segmentation
Chapter 10: Representation and Description
Chapter 11: Object Recognition
Chapter 12: Wavelets and Multiresolution Processing

The book is published by Tata McGraw Hill Education and has received positive reviews from readers and experts. It is suitable for undergraduate and postgraduate courses in engineering and computer science as well as for self-study and reference.

One of the main features of the book is its illustrative approach, which uses numerous figures, tables and diagrams to explain the concepts and techniques of image processing. The book also provides several practical examples and case studies to demonstrate the applications of image processing in various domains such as face recognition, fingerprint recognition, iris recognition, license plate recognition, medical image analysis, satellite image analysis and more.
Another feature of the book is its MATLAB applications, which are given at the end of each chapter. These applications help the readers to implement the algorithms and methods discussed in the book using MATLAB, a popular software tool for numerical computation and visualization. The MATLAB code and images used in the book are also available online for download.
The book is written in a simple and lucid style that makes it easy to read and understand. The authors have used a logical and systematic approach to present the topics and have avoided unnecessary mathematical details and derivations. The book also contains review questions, multiple choice questions and exercises at the end of each chapter to test the readers' comprehension and reinforce their learning. 9d9bd590cd

Digital Image Processing By Jayaraman S, Veerakumar T, Esakkirajan S

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Digital Image Processing By Jayaraman S, Veerakumar T, Esakkirajan S

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Image compression is a type of data compression applied to digital images to minimize the size in bytes of an image file without degrading the quality of image to an unacceptable level. It involves the minimization of the number of information carrying unit pixel (i.e., reducing spatial redundancy). Reduction in file size allows a number of images to be stored in a limited storage space and also reduces time required for image to be sent over network. Two types of compression techniques exist, lossy and lossless.[2] In lossy image compression scheme, certain amount of information is discarded (that is some data are lost), and hence, image cannot be decompressed 100% with originality. In lossless image compression, no data is lost and thus this method of image compression allows the original image to be perfectly reconstructed from the compressed data. We choose to work on the lossy image compression techniques with hope that we will get a very good compression without loss of clinical details for NM images.


Vision is the most powerful of the five human senses. Visual information, conveyed in the form of imagesgives better impact than textual information. The fields of digital image processing have grown tremendouslyover the past 30 years. The growth of digital image processing has been fueled by technological advancesin digital imaging, computer processors and mass storage devices. Research and development of image processingtechnologies have advanced very rapidly in the past decade. Digital image processing is concernedprimarily with the extraction of useful information from images. In this process, it also deals with 1) imagerepresentation, 2) enhancing the quality of an image, 3) restoration of the original image from its degradedversion, and 4) compression of the large amount of data in the images for efficient archiving and retrieval.Image-processing algorithms can be classified into three different categories. At the lowest level, the algorithmdeals directly with the raw pixel values (image denoising and edge detection are good examples). In themiddle level, the algorithm utilises low-level results for processes such as segmentation and edge linking.At the highest level, the algorithm attempts to extract semantic information from those provided by the lowerlevels. Examples of high-level algorithms are handwriting recognition, face recognition and machine visionalgorithms. The objective of this book is to not only introduce different concepts of digital image processingto undergraduate and postgraduate students but also to serve as a handbook for practicing engineers.
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