Publication

A model for colour prediction of halftoned samples incorporating light scattering and ink spreading

Roger Hersch, Patrick Emmel
1999
Conference Papers

Abstract

A model for color prediction of halftoned samples incorporating light scattering and ink spreading was presented. The spreading process was modeled by enlarging the drop impact according to the configuration of its neighbors and the state of the surface. The spectra of halftoned samples produced with one ink were predicted with an average prediction error or about δE=1.4 in CIELAB. For two halftoned ink layers, good spectral predictions were achieved with an average error of about δE=2.1 in CIELAB.

Official source

https://infoscience.epfl.ch/entities/publication/cd18726c-5446-468a-9cb2-052d3b4a8192

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Roger Hersch, Patrick Emmel
1999
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/cd18726c-5446-468a-9cb2-052d3b4a8192

About this result

Related concepts (32)

Mean squared error

In statistics, the mean squared error (MSE) or mean squared deviation (MSD) of an estimator (of a procedure for estimating an unobserved quantity) measures the average of the squares of the errors—that is, the average squared difference between the estimated values and the actual value. MSE is a risk function, corresponding to the expected value of the squared error loss. The fact that MSE is almost always strictly positive (and not zero) is because of randomness or because the estimator does not account for information that could produce a more accurate estimate.

Additive color

Additive color or additive mixing is a property of a color model that predicts the appearance of colors made by coincident component lights, i.e. the perceived color can be predicted by summing the numeric representations of the component colors. Modern formulations of Grassmann's laws describe the additivity in the color perception of light mixtures in terms of algebraic equations. Additive color predicts perception and not any sort of change in the photons of light themselves.

Mean absolute error

In statistics, mean absolute error (MAE) is a measure of errors between paired observations expressing the same phenomenon. Examples of Y versus X include comparisons of predicted versus observed, subsequent time versus initial time, and one technique of measurement versus an alternative technique of measurement. MAE is calculated as the sum of absolute errors divided by the sample size: It is thus an arithmetic average of the absolute errors , where is the prediction and the true value.

Related publications (1)

A model for colour prediction of halftoned samples incorporating light scattering and ink spreading

Chat with Graph Search

Fast Prototyping of Reconfigurable Architectures: An Estimation and Exploration Methodology from System-Level Specifications