Third generation book that builds on two highly successful earlier editions and the author's twenty years of academic and industrial experience in image processing. Reflects new trends; document image compression and data compression standards.
This book was designed specifically to be used in advanced computer imaging classes, and taught by a professor (as in only a professor that has worked for years on the material can translate some of the text).
The first 3 chapters are well written and a self-starter (such as myself) can clearly understand the concepts and the application of the material given.
After chapter 3 (4+) this book becomes a stinking pile of shit. The problem lies in the ability to explain the transition from image domain to frequency domain through usage of the Fourier (four-ee-eh) series (specifically DFT/FFT). Using the Fourier series is the MOST important aspect of the book, but the authors do such a terrible job of showing application of the enormous amount of math presented that one is left scratching their head.
I can say (after spending money and time on the book), that if you are a self-learner then steer clear of this book until you find an internet site somewhere that explains Fourier series and application of both DFT/FFT. Then this book might be a good reference.
This book offers a good understanding of the foundations of digital image processing and provides enough mathematics for learning concepts behind different techniques and algorithms.
A good thing about this book is that it uses a lot of figures and examples which makes reading easy.
Contents have good orders so you will be completely ready when you jump to the next topic.
It usually after explaining a subject, refers to new techniques that are used in image processing, so you gain good sight about new and efficient methods.
I used this book when I had digital image processing course and I think it's not a good idea to take this book for self learning unless you have some previous knowledge.
I had some problems with chapter 4 and unlike other parts, I read it twice to catch all subjects. It's hard to explain Fourier's transform and image in the frequency domain in one chapter but authors did it but the rest of the book is written fluently.
A really great introduction to image processing and analysis. The majority of the data I collect in in my graduate program are images and videos. I was using some programs based in ImageJ, but without a better understanding of the theory and method behind image analysis is like walking in the dark.
The textbook comes with a useful toolbox of MatLab functions. I’m more of a Python guy myself, but hey. It’s easy to go back and forth. I was most interested in segmentation methods when I started, and it does a great job of explaining these in the later chapters of the book.
As expected, the material in here requires a good background in matrix math, so be prepared.
The mathematics is not rigorous, and given in a too factual way....but was a good read definitely...made an app named upix(currently at beta in PlayStore), all thanks to this book!
The content and structure are very good. Some parts of the book need more clarifications. FFT and Wavelet transformation are not for DIP beginners and require some knowledge from DSP. A good book overall.
Not recommended for math newbies, too much mathematical info that needs external references, some points are not explained well, gives overall ideas about image processing and discrete digital signal processing basics.
great books, I never learn about Digital Image Processing before when my lecturer proposed us to read this book. It give me a good basic about Digital Image Processing :) Really help.
The textbook of my university image processing elective. It was the most fun CS course I ever took. I slept with photocopies of this textbook on my bed. We were inseparable!