Guide to Signals and Patterns in Image Processing - Das, Apurba

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Résumé :
This text reviews the field of digital image processing from the different perspectives offered by the separate domains of signal processing and pattern recognition. The book describes a rich array of applications, representing the latest trends in industry and academic research. To inspire further interest in the field, a selection of worked-out numerical problems is also included in the text. The content is presented in an accessible manner, examining each topic in depth without assuming any prior knowledge from the reader, and providing additional background material in the appendices. Features: covers image enhancement techniques in the spatial domain, the frequency domain, and the wavelet domain; reviews compression methods and formats for encoding images; discusses morphology-based image processing; investigates the modeling of object recognition in the human visual system; provides supplementary material, including MATLAB and C++ code, and interactive GUI-based modules, at an associated website.

Biographie:
Apurba Das is a Technical Specialist in the Image Processing Lab at HCL Technologies, Chennai, India. He has previously served as a Scientist in the Advanced Image Processing Lab at the Centre for Development of Advanced Computing, a R&D organization of the Indian Government Ministry of Communications and Information Technology. His other Springer publications include the books Signal Conditioning: An Introduction to Continuous Wave Communication and Signal Processing and Digital Communication: Principles and System Modelling....

Sommaire:

Introduction to Digital Images

Image Enhancement in the Spatial Domain

Interpretation and Processing of Images in the Frequency Domain

Color Science and Color Technology

Wavelets: Multi-Resolution Image Processing

Compression and Encoding of Images: Image Formats

Morphology-Based Image Processing

Patterns in Images and their Applications

Psycho-Visual Pattern Recognition: Computer Vision

Appendix A: Digital Differentiation and Edge Detection

Appendix B: Elementary Probability Theory

Appendix C: Frequently Used MATLAB Functions