Advances in Image and Signal Processing
Signal processing is an electrical engineering subfield that focuses on analysing, modifying, and synthesizing signals such as sound, images, and scientific measurements. Signal processing techniques can be used to improve transmission, storage efficiency and subjective quality and to also emphasize or detect components of interest in a measured signal. Digital image processing is the use of a digital computer to process digital images through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and distortion during processing. Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems. The generation and development of digital image processing are mainly affected by three factors: first, the development of computers; second, the development of mathematics (especially the creation and improvement of discrete mathematics theory); third, the demand for a wide range of applications in environment, agriculture, military, industry and medical science has increased.
Components of the Book:
  • Chapter 1
    Motor unit action potential conduction velocity estimated from surface electromyographic signals using image processing techniques
  • Chapter 2
    Automatic self-correcting in signal processing for magnetic resonance spectroscopy: noise reduction, resolution improvement and splitting overlapped peaks
  • Chapter 3
    Signal processing in urodynamics: towards high definition urethral pressure profilometry
  • Chapter 4
    Compressed sensing MRI: a review from signal processing perspective
  • Chapter 5
    The promise of social signal processing for research on decision-making in entrepreneurial contexts
  • Chapter 6
    Frame-based Programming, Stream-Based Processing for Medical Image Processing Applications
  • Chapter 7
    New pediatric vision screener, part II: electronics, software, signal processing and validation
  • Chapter 8
    FPGA-Based Soft-Core Processors for Image Processing Applications
  • Chapter 9
    Twofold processing for denoising ultrasound medical images
  • Chapter 10
    The perceptual processing of fused multi-spectral imagery
  • Chapter 11
    Joint pre-processing framework for two-dimensional gel electrophoresis images based on nonlinear filtering, background correction and normalization techniques
  • Chapter 12
    Recent advances ofthe signal processing techniques infuture smart grids
  • Chapter 13
    Dynamic and robust method for detection and locating vehicles in the video images sequences with use of image processing algorithm
  • Chapter 14
    Machine learning applied to retinal image processing for glaucoma detection: review and perspective
  • Chapter 15
    Image processing for identification and quantification of filamentous bacteria in in situ acquired images
Readership: Students, academics, teachers and other people attending or interested in Image and Signal Processing.
Mario Klünder
Institute for System Dynamics, University of Stuttgart, Waldburgstr. Germany

Werner Liebregts
Jheronimus Academy of Data Science, ‘s-Hertogenbosch, The Netherlands

Zaid Al-Ars
Computer Engineering Laboratory, Delft University of Technology, Delft, The Netherlands

Boris I. Gramatikov
Laboratory of Ophthalmic Instrument Development, The Krieger Children’s Eye Center at the Wilmer Eye Institute, The Johns Hopkins University School of Medicine, USA

Dževad Belkić
Department of Oncology-Pathology, Karolinska Institute, Stockholm, Sweden

and more...
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