Digital Image Processing by Sanjay Sharma: A Comprehensive Guide for Students and Professionals
Digital image processing is the field of study that deals with manipulating and enhancing images using computer algorithms. It has applications in various domains such as medicine, engineering, security, entertainment, and more. Digital image processing can help improve the quality, resolution, contrast, and color of images, as well as extract useful information from them.
One of the best books to learn digital image processing is Digital Image Processing by Sanjay Sharma. This book covers the fundamental concepts and techniques of digital image processing in a clear and concise manner. It also provides numerous examples and exercises to help readers understand and apply the concepts.
Some of the topics covered in this book are:
digital image processing book by sanjay sharma pdf download
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Introduction to digital image processing
Digital image fundamentals
Image enhancement in spatial and frequency domains
Image restoration
Image segmentation
Image compression
Image representation and description
Object recognition
Morphological image processing
Color image processing
The book is suitable for undergraduate and postgraduate students of computer science, electronics, and communication engineering. It can also be used as a reference book by professionals and researchers working in the field of digital image processing.
If you want to download the PDF version of this book, you can visit the following websites:
Digital Image Processing - Sanjay Sharma - Google Books[^1^]
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Digital Image Processing Book By Sanjay Sharma Pdf ((FREE)) Download[^3^]
We hope you find this book useful and informative. Happy reading!
In this section, we will give a brief overview of some of the topics covered in the book Digital Image Processing by Sanjay Sharma.
Introduction to Digital Image Processing
Digital image processing is the process of manipulating and enhancing digital images using computer algorithms. A digital image is a representation of a two-dimensional scene using a finite number of pixels. Each pixel has a numerical value that indicates its brightness or color. Digital image processing can be classified into two categories: low-level and high-level. Low-level image processing involves operations such as noise removal, contrast enhancement, and edge detection. High-level image processing involves operations such as object recognition, face detection, and scene understanding.
Digital Image Fundamentals
This chapter introduces the basic concepts and terminology of digital image processing. It covers topics such as image sampling and quantization, image resolution and size, image formats and standards, image arithmetic and logic operations, image histograms and statistics, and image transforms. It also explains the difference between spatial and frequency domains, and how to convert an image from one domain to another using Fourier transform.
Image Enhancement in Spatial and Frequency Domains
Image enhancement is the process of improving the visual quality of an image by modifying its pixel values. Image enhancement can be done in either spatial or frequency domains. Spatial domain methods operate directly on the pixel values of an image, while frequency domain methods operate on the Fourier transform of an image. Some of the techniques for image enhancement are contrast stretching, histogram equalization, smoothing filters, sharpening filters, homomorphic filtering, and frequency domain filtering. 0efd9a6b88
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