This book dissects a very common but important image processing application: digital image denoising. The dissection begins with the most fundamental of digital images, noise sources, and the effect of noise on different image features. A variety of denoising techniques are reviewed, analyzed, and compared in this book to provide the readers with a complete picture of digital image denoising. The book has placed special emphasis on the theory behind each algorithm and how it can be for real world application.
* Excellent explanatory introduction to image denoising methods;
* thorough treatment of the theoretical foundations, with comprehensive analytical analysis of each presented algorithm;
* discussion in detail - including the assumptions and limitations - of each presented algorithm;
* detail devoted to MATLAB(r) implementation of the presented algorithm;
* coverage of classical denoising methods, and advanced model based denoising methods;
* simulation results are presented for comparative analysis;
* summary of important results obtained in each chapter given at its end; and
* theoretical, analytical, and computational exercises are provided at the end of each chapter.
MATLAB code, solution manual, and PPT for lecturing will be provided.
Presents a review of image denoising algorithms with practical MATLAB implementation guidance
Digital Image Denoising in MATLAB provides a comprehensive treatment of digital image denoising, containing a variety of techniques with applications in high-quality photo enhancement as well as multi-dimensional signal processing problems such as array signal processing, radar signal estimation and detection, and more. Offering systematic guidance on image denoising in theories and in practice through MATLAB, this hands-on guide includes practical examples, chapter summaries, analytical and programming problems, computer simulations, and source codes for all algorithms discussed in the book.
The book explains denoising algorithms including linear and nonlinear filtering, Wiener filtering, spatially adaptive and multi-channel processing, transform and wavelet domains processing, singular value decomposition, and various low variance optimization and low rank processing techniques. Throughout the text, the authors address the theory, analysis, and implementation of the denoising algorithms to help readers solve their image processing problems and develop their own solutions.
- Explains how the quality of an image can be quantified in MATLAB
- Discusses what constitutes a "naturally looking" image in subjective and analytical terms
- Presents denoising techniques for a wide range of digital image processing applications
- Describes the use of denoising as a pre-processing tool for various signal processing applications or big data analysis
- Requires only a fundamental knowledge of digital signal processing
- Includes access to a companion website with source codes, exercises, and additional resources
Digital Image Denoising in MATLAB is an excellent textbook for undergraduate courses in digital image processing, recognition, and statistical signal processing, and a highly useful reference for researchers and engineers working with digital images, digital video, and other applications requiring denoising techniques.
