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Computational Color Imaging

Overview of attention for book
Cover of 'Computational Color Imaging'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Color Information Processing in Higher Brain Areas
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    Chapter 2 Spatio-temporal Tone Mapping Operator Based on a Retina Model
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    Chapter 3 Colour Representation in Lateral Geniculate Nucleus and Natural Colour Distributions
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    Chapter 4 Color Constancy Algorithm Selection Using CART
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    Chapter 5 Illuminant Change Estimation via Minimization of Color Histogram Divergence
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    Chapter 6 Illumination Chromaticity Estimation Based on Dichromatic Reflection Model and Imperfect Segmentation
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    Chapter 7 An Improved Image Re-indexing Technique by Self Organizing Motor Maps
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    Chapter 8 KANSEI Based Clothing Fabric Image Retrieval
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    Chapter 9 A New Spatial Hue Angle Metric for Perceptual Image Difference
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    Chapter 10 Structure Tensor of Colour Quaternion Image Representations for Invariant Feature Extraction
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    Chapter 11 Non-linear Filter Response Distributions of Natural Colour Images
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    Chapter 12 Perceptual Color Correction: A Variational Perspective
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    Chapter 13 A Computationally Efficient Technique for Image Colorization
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    Chapter 14 Texture Sensitive Denoising for Single Sensor Color Imaging Devices
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    Chapter 15 Color Reproduction Using Riemann Normal Coordinates
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    Chapter 16 Classification of Paper Images to Predict Substrate Parameters Prior to Print
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    Chapter 17 A Colorimetric Study of Spatial Uniformity in Projection Displays
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    Chapter 18 Color Stereo Matching Cost Applied to CFA Images
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    Chapter 19 JBIG for Printer Pipelines: A Compression Test
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    Chapter 20 Synthesis of Facial Images with Foundation Make-Up
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    Chapter 21 Polynomial Regression Spectra Reconstruction of Arctic Charr’s RGB
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    Chapter 22 An Adaptive Tone Mapping Algorithm for High Dynamic Range Images
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    Chapter 23 Material Classification for Printed Circuit Boards by Spectral Imaging System
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    Chapter 24 Supervised Local Subspace Learning for Region Segmentation and Categorization in High-Resolution Satellite Images
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

patent
1 patent
wikipedia
1 Wikipedia page

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
2 Mendeley
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Title
Computational Color Imaging
Published by
ADS, July 2009
DOI 10.1007/978-3-642-03265-3
ISBNs
978-3-64-203264-6, 978-3-64-203265-3
Editors

Trémeau, Alain, Schettini, Raimondo, Tominaga, Shoji

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 50%
Researcher 1 50%
Readers by discipline Count As %
Computer Science 1 50%
Engineering 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 February 2024.
All research outputs
#5,444,342
of 25,389,532 outputs
Outputs from ADS
#3,597
of 26,144 outputs
Outputs of similar age
#22,974
of 122,245 outputs
Outputs of similar age from ADS
#46
of 305 outputs
Altmetric has tracked 25,389,532 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 26,144 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has done well, scoring higher than 82% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 122,245 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 305 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.