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Related Concept Videos

Histogram01:05

Histogram

12.7K
The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
A histogram graph consists of contiguous (adjoining) boxes. The heights of the bars correspond to frequency values. The graph will have the same shape with respective labels. The...
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Probability Histograms01:17

Probability Histograms

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A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
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Relative Frequency Histogram01:14

Relative Frequency Histogram

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The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. Like the histogram, a relative frequency histogram also has the same shape with a horizontal scale (the x-axis), but the vertical scale (the y-axis) is marked with relative frequencies (percentages of the whole) instead of actual frequencies. A relative frequency histogram is a graphical representation of a frequency distribution where the...
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Upsampling01:22

Upsampling

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Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
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Fast Hue and Range Preserving Histogram: Specification: Theory and New Algorithms for Color Image Enhancement.

Mila Nikolova, Gabriele Steidl

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    Summary
    This summary is machine-generated.

    Simple algorithms enhance color images while preserving hue and RGB channel range. These methods improve chromaticity and outperform existing techniques, offering a competitive solution for hue-preserving image enhancement.

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    Area of Science:

    • Digital Imaging and Computer Vision
    • Image Processing and Enhancement

    Background:

    • Color image enhancement is a challenging task with numerous applications.
    • Maintaining the original hue is critical for many image enhancement scenarios.
    • Existing methods may struggle with optimal hue and color range preservation.

    Purpose of the Study:

    • To propose simple, effective image enhancement algorithms.
    • To ensure algorithms conserve hue and optimally preserve the RGB channel range (gamut).
    • To develop a novel color assignment methodology for enhanced images.

    Main Methods:

    • Transformation of the input intensity image to a target intensity image with a specified histogram.
    • Derivation of a new color assignment methodology to match the enhanced image to the target intensity.
    • Analysis of algorithms based on chromaticity improvement and comparison with the Naik-Murthy algorithm.

    Main Results:

    • The proposed algorithms effectively conserve hue and preserve the RGB channel range.
    • Numerical tests confirm theoretical results, demonstrating superior performance over the Naik-Murthy algorithm.
    • The algorithms achieve competitive results compared to established methods, particularly for hue-sensitive images.

    Conclusions:

    • The developed simple algorithms offer significant improvements in color image enhancement.
    • Hue conservation and optimal gamut preservation are achieved effectively.
    • These methods provide a valuable alternative for applications requiring high-fidelity color reproduction.