1.

Record Nr.

UNINA9910299701803321

Autore

Deng Yue

Titolo

High-Dimensional and Low-Quality Visual Information Processing : From Structured Sensing and Understanding / / by Yue Deng

Pubbl/distr/stampa

Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2015

ISBN

3-662-44526-3

Edizione

[1st ed. 2015.]

Descrizione fisica

1 online resource (108 p.)

Collana

Springer Theses, Recognizing Outstanding Ph.D. Research, , 2190-5053

Disciplina

005.74

006.312

006.37

006.6

Soggetti

Signal processing

Image processing

Speech processing systems

Optical data processing

Data structures (Computer science)

Data mining

Signal, Image and Speech Processing

Image Processing and Computer Vision

Data Structures and Information Theory

Data Mining and Knowledge Discovery

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Introduction -- Sparse Structure for Visual Signal Sensing -- Graph Structure for Visual Signal Sensing -- Discriminative Structure for Visual Signal Understanding -- Information Theoretic Structure for Visual Signal Understanding -- Conclusions.

Sommario/riassunto

This thesis primarily focuses on how to carry out intelligent sensing and understand the high-dimensional and low-quality visual information. After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive



range of mathematical topics, including compressive sensing, graph theory, probabilistic learning and information theory. These computational models are also applied to address a number of real-world problems including biometric recognition, stereo signal reconstruction, natural scene parsing, and SAR image processing.