Digital Signal Processing has undergone enormous growth in usage/implementation in the last 20 years and many engineering schools are now offering real-time DSP courses in their undergraduate curricula. Our everyday lives involve the use of DSP systems in things such as cell phones and high-speed modems; Texas Instruments has introduced the TMS320C6000 DSP processor family to meet the high performance demands of today s signal processing applications.
This book provides the know-how for the implementation and optimization of computationally intensive signal processing algorithms on the Texas Instruments family of TMS320C6000 DSP processors. It is organized in such a way that it can be used as the textbook for DSP lab courses offered at many engineering schools or as a self-study/reference for those familiar with DSP but not this family of processors.
This book provides a restructured, modified, and condensed version of the information in more than twenty TI manuals so that one can learn real-time DSP implementations on the C6000 family in a structured course, within one semester. Each chapter is followed by an appropriate lab exercise to provide the hands-on lab material for implementing appropriate signal processing
functions. These labs are included on the accompanying companion website to take the reader through the entire process of C6X code writing.
* Each chapter is followed by an appropriate lab exercise
* Provides the hands-on lab material for implementing appropriate signal processing functions
* Labs are included on accompanying companion website taking the reader through the entire process of C6X code writing"

This book combines textual and graphical programming to form a hybrid programming approach, enabling a more effective means of building and analyzing DSP systems. The hybrid programming approach allows the use of previously developed textual programming solutions to be integrated into LabVIEW's highly interactive and visual environment, providing an easier and quicker method for building DSP systems. This book will be an ideal introduction for engineers and students seeking to develop DSP systems in quick time.
Features
- The only DSP laboratory book that combines textual and graphical programming
- 12 lab experiments that incorporate C/MATLAB code blocks into the LabVIEW graphical programming environment via the MathScripting feature
- Lab experiments covering basic DSP implementation topics including sampling, digital filtering, fixed-point data representation, frequency domain processing
- Interesting applications using the hybrid programming approach, such as a software-defined radio system, a 4-QAM Modem, and a cochlear implant simulator
- CD providing all the lab codes
Nasser Kehtarnavaz is Professor of Electrical Engineering at University of Texas at Dallas. He has written numerous papers and five other books pertaining to signal and image processing, and regularly teaches digital signal processing laboratory courses, for which this book is intended. Among his many professional activities, he is Coeditor-in-Chief of Journal of Real-Time Image Processing, and Chair of the Dallas Chapter of the IEEE Signal Processing Society. Dr. Kehtarnavaz is a Fellow of SPIE, a Senior Member of IEEE, and a Professional Engineer.
* The only DSP project book thatcombines textual and graphical programming
* 12 Lab projects that incorporate MATLAB code blocks into the LabVIEW graphical programming environment via the MathScripting feature.
* Interesting applications such as the design of a cochlear implant simulator and a software-defined radio system.

Image fusion in remote sensing or pansharpening involves fusing spatial (panchromatic) and spectral (multispectral) images that are captured by different sensors on satellites. This book addresses image fusion approaches for remote sensing applications. Both conventional and deep learning approaches are covered. First, the conventional approaches to image fusion in remote sensing are discussed. These approaches include component substitution, multi-resolution, and model-based algorithms. Then, the recently developed deep learning approaches involving single-objective and multi-objective loss functions are discussed. Experimental results are provided comparing conventional and deep learning approaches in terms of both low-resolution and full-resolution objective metrics that are commonly used in remote sensing. The book is concluded by stating anticipated future trends in pansharpening or image fusion in remote sensing.

This book presents an overview of the guidelines and strategies for transitioning an image or video processing algorithm from a research environment into a real-time constrained environment. Such guidelines and strategies are scattered in the literature of various disciplines including image processing, computer engineering, and software engineering, and thus have not previously appeared in one place. By bringing these strategies into one place, the book is intended to serve the greater community of researchers, practicing engineers, industrial professionals, who are interested in taking an image or video processing algorithm from a research environment to an actual real-time implementation on a resource constrained hardware platform. These strategies consist of algorithm simplifications, hardware architectures, and software methods. Throughout the book, carefully selected representative examples from the literature are presented to illustrate the discussed concepts. After reading the book, the readers are exposed to a wide variety of techniques and tools, which they can then employ to design a real-time image or video processing system.

Field Programmable Gate Arrays (FPGAs) are increasingly becoming the platform of choice to implement DSP algorithms. This book is designed to allow DSP students or DSP engineers to achieve FPGA implementation of DSP algorithms in a one-semester DSP laboratory course or in a short design cycle time based on the LabVIEW FPGA Module.Features: - The first DSP laboratory book that uses the FPGA platform instead of the DSP platform for implementation of DSP algorithms- Incorporating introductions to LabVIEW and VHDL- Lab experiments covering FPGA implementation of basic DSP topics including convolution, digital filtering, fixed-point data representation, adaptive filtering, frequency domain processing- Hardware FPGA implementation applications including wavelet transform, software-defined radio, and MP3 player- Website providing downloadable LabVIEW FPGA codes