Examples in Code Composer Studio(tm) and MATLAB
Buch, Englisch, 433 Seiten, Format (B × H): 165 mm x 244 mm, Gewicht: 1780 g
ISBN: 978-0-387-25280-3
Verlag: Springer Us
Embedded Image Processing on the TMS320C6000™ DSP: Examples in Code Composer Studio™ and MATLAB focuses on efficient implementations of advanced image processing algorithms for resource-constrained embedded DSP systems. Featuring the popular Texas Instruments TMS320C6000TM line of Digital Signal Processors, it utilizes a proven methodology of beginning with a high-level algorithmic point-of-view, proceeding to develop prototype code in MATLAB and Visual Studio, and concluding with an efficient implementation suitable for deployment on an embedded DSP system.
Aside from image processing, the author also explains the uses and rationale behind a plethora of technologies, most notably several industry-standard and essential TI developer technologies, including the Code Composer Studio™ IDE. Highlights include numerous debugged MATLAB and C/C++ Visual Studio prototype applications and efficient C implementations of real-world algorithms tested on both the C6416 DSK and C6701 EVM development platforms.
Embedded Image Processing on the TMS320C6000™ DSP: Examples in Code Composer Studio™ and MATLAB is an essential book for professional signal & image processing engineers working with TI DSPs where real-time constraints are present and performance is at a premium. Imaging software developers and DSP users will also find this book applicable, as it covers a variety of image and signal processing building blocks that appear in a diverse set of real-world applications, including medical imaging, satellite imaging, digital photography, and pattern recognition, to name a few. It may also serve as a reference work for advanced image processing, computer vision, and DSP students working in labs that use TI development kits or MATLAB.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction.- Tools.- Spatial Processing Techniques.- Image Filtering.- Edge Detection and Segmentation.- Wavelets.- Appendix A Putting it together: a streaming video application.- Appendix B Code Optimization.
