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  2. Digital image processing - Wikipedia

    en.wikipedia.org/wiki/Digital_image_processing

    Many of the techniques of digital image processing, or digital picture processing as it often was called, were developed in the 1960s, at Bell Laboratories, the Jet Propulsion Laboratory, Massachusetts Institute of Technology, University of Maryland, and a few other research facilities, with application to satellite imagery, wire-photo standards conversion, medical imaging, videophone ...

  3. Nyquist–Shannon sampling theorem - Wikipedia

    en.wikipedia.org/wiki/Nyquist–Shannon_sampling...

    The sampling theorem applies to camera systems, where the scene and lens constitute an analog spatial signal source, and the image sensor is a spatial sampling device. Each of these components is characterized by a modulation transfer function (MTF), representing the precise resolution (spatial bandwidth) available in that component.

  4. Sample-rate conversion - Wikipedia

    en.wikipedia.org/wiki/Sample-rate_conversion

    Application areas include image scaling [2] and audio/visual systems, where different sampling rates may be used for engineering, economic, or historical reasons. For example, Compact Disc Digital Audio and Digital Audio Tape systems use different sampling rates, and American television, European television, and movies all use different frame ...

  5. Reconstruction filter - Wikipedia

    en.wikipedia.org/wiki/Reconstruction_filter

    A subtlety in image processing is that (linear) signal processing assumes linear luminance – that doubling a pixel value doubles the luminance of the output. However, images are frequently gamma encoded, notably in the sRGB color space, so luminance is not linear. Thus to apply a linear filter, one must first gamma decode the values – and ...

  6. Oversampling - Wikipedia

    en.wikipedia.org/wiki/Oversampling

    In signal processing, oversampling is the process of sampling a signal at a sampling frequency significantly higher than the Nyquist rate. Theoretically, a bandwidth-limited signal can be perfectly reconstructed if sampled at the Nyquist rate or above it. The Nyquist rate is defined as twice the bandwidth of the signal.

  7. Sampling (signal processing) - Wikipedia

    en.wikipedia.org/wiki/Sampling_(signal_processing)

    In signal processing, sampling is the reduction of a continuous-time signal to a discrete-time signal. A common example is the conversion of a sound wave to a sequence of "samples". A sample is a value of the signal at a point in time and/or space; this definition differs from the term's usage in statistics, which refers to a set of such values ...

  8. Nyquist frequency - Wikipedia

    en.wikipedia.org/wiki/Nyquist_frequency

    In this example, f s is the sampling rate, and 0.5 cycle/sample × f s is the corresponding Nyquist frequency. The black dot plotted at 0.6 f s represents the amplitude and frequency of a sinusoidal function whose frequency is 60% of the sample rate. The other three dots indicate the frequencies and amplitudes of three other sinusoids that ...

  9. Pyramid (image processing) - Wikipedia

    en.wikipedia.org/wiki/Pyramid_(image_processing)

    Visual representation of an image pyramid with 5 levels. Pyramid, or pyramid representation, is a type of multi-scale signal representation developed by the computer vision, image processing and signal processing communities, in which a signal or an image is subject to repeated smoothing and subsampling.