Amazon cover image
Image from Amazon.com

Digital image processing / Rafael C. Gonzalez and Richard E. Woods

By: Contributor(s): Material type: TextTextPublication details: India Pearson Education 2018Edition: 4th edDescription: 1019 pISBN:
  • 9789353062989
Subject(s): DDC classification:
  • 621.367 GON-R
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Collection Shelving location Call number Status Date due Barcode Item holds
Course Text Book Course Text Book BITS Pilani Hyderabad 621 Text & Reference Section (Student cannot borrow these books) 621.367 GON-R (Browse shelf(Opens below)) Available 38252
Total holds: 0
Browsing BITS Pilani Hyderabad shelves, Shelving location: Text & Reference Section (Student cannot borrow these books), Collection: 621 Close shelf browser (Hides shelf browser)
621.367 GON-R Digital image processing / 621.367 GON-R Digital image processing / 621.367 GON-R Digital image processing / 621.367 GON-R Digital image processing / 621.367 GON-R Digital image processing using MATLAB / 621.3678 BHA-B Remote sensing and GIS / 621.3678 BHA-B Remote sensing and GIS /

The fourth edition of, which celebrates the book’s 40th anniversary, continues its cutting-edge
focus on contemporary developments in all mainstream areas of image processing. It focuses on material that is
fundamental and has a broad scope of application. 1. Coverage of graph cuts and their application to segmentation.
2. A discussion of super pixels and their use in region segmentation.
3. 425 New images, 135 New drawings, 220 New exercises and 120 Matlab projects.
4. Two New chapters:
a. A chapter dealing with active contours for image segmentation, including snakes and level sets.
b. A chapter that brings together wavelets, several New transforms and many of the image transforms that were scattered throughout the book.
5. A complete update of the image pattern recognition chapter to incorporate New material on deep neural networks, backpropagation, deep learning and especially, deep convolutional neural networks.
6. Coverage of feature extraction, including the Scale Invariant Feature Transform (SIFT, maximally stable extremal regions (MSERs) and corner detection.
7. Coverage of the fundamentals of spatial filtering, image transforms and finite differences with a focus on edge detection.
Chapter 1 Introduction
Chapter 2 Digital Image Fundamentals
Chapter 3 Intensity Transformations and Spatial Filtering
Chapter 4 Filtering in the Frequency Domain
Chapter 5 Image Restoration and Reconstruction
Chapter 6 Wavelet and Other Image Transforms
Chapter 7 Colour Image Processing
Chapter 8 Image Compression and Watermarking
Chapter 9 Morphological Image Processing
Chapter 10 Image Segmentation I: Edge Detection,
Chapter 11 Image Segmentation II: Active Contours: Snakes and Level Sets
Chapter 12 Feature Extraction
Chapter 13 Image Pattern Classification.

There are no comments on this title.

to post a comment.
An institution deemed to be a University Estd. Vide Sec.3 of the UGC
Act,1956 under notification # F.12-23/63.U-2 of Jun 18,1964

© 2024 BITS-Library, BITS-Hyderabad, India.