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Journal ArticleDOI

A Simple Autocorrelation Algorithm for Determining Grain Size from Digital Images of Sediment

David M. Rubin
- 01 Jan 2004 - 
- Vol. 74, Iss: 1, pp 160-165
TLDR
Autocorrelation between pixels in digital images of sediment can be used to measure average grain size of sediment on the bed, grain-size distribution of bed sediment, and vertical profiles in grain size in a cross-sectional image through a bed as discussed by the authors.
Abstract
Autocorrelation between pixels in digital images of sediment can be used to measure average grain size of sediment on the bed, grain-size distribution of bed sediment, and vertical profiles in grain size in a cross-sectional image through a bed. The technique is less sensitive than traditional laboratory analyses to tails of a grain-size distribution, but it offers substantial other advantages: it is 100 times as fast; it is ideal for sampling surficial sediment (the part that interacts with a flow); it can determine vertical profiles in grain size on a scale finer than can be sampled physically; and it can be used in the field to provide almost real-time grain-size analysis. The technique can be applied to digital images obtained using any source with sufficient resolution, including digital cameras, digital video, or underwater digital microscopes (for real-time grain-size mapping of the bed).

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Citations
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TL;DR: A methodology is proposed to assess the metrological performances of the image processing algorithms that constitute their main component, the knowledge of which being required for a global assessment of the whole measurement system.
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Large-scale dam removal on the Elwha River, Washington, USA: River channel and floodplain geomorphic change

TL;DR: The authors investigated the downstream effects of sediment released during the largest dam removal in history, on the Elwha River, Washington, USA, by measuring changes in riverbed elevation and topography, bed sediment grain size, and channel planform as two dams were removed in stages over two years.
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Concepts in gravel beach dynamics

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References
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Book

Principles, Methods and Application of Particle Size Analysis

TL;DR: Syvitski et al. as mentioned in this paper proposed a method for grain size analysis in marine geotechnical studies using laser diffraction and suite statistics, and applied suite statistics to stratigraphy and sea-level changes.
Book ChapterDOI

Principles, methods, and application of particle size analysis: Principles and methods of geological particle size analysis

TL;DR: A detailed survey of the state-of-the-art in particle size measurement can be found in this paper, where the authors provide a detailed analysis of the properties used as measures of particle size.
Book ChapterDOI

Principles, methods, and application of particle size analysis: Laser diffraction size analysis

TL;DR: In this paper, the authors proposed a method to infer the size distributions of fine particles from the angular distribution of the intensity of forward-scattered coherent light (Cornillault, 1972; Weiss & Frock, 1976; Swithenbank et al., 1977).
Journal ArticleDOI

Automated extraction of grain-size data from gravel surfaces using digital image processing

TL;DR: The research shows that it can be used to map and quantify very rapidly spatial variations in grain-size characteristics, although it cannot deal with the longrecognised problem of the relationship between two-dimensional planformgrain-size estimates and actual a- and b- axes obtained by direct grain sampling.
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