Color induction: Spatial gain of regional retinal disinhibition in different color channels

1988 ◽  
Vol 75 (11) ◽  
pp. 574-575 ◽  
Author(s):  
S. Brandt ◽  
M. Reiser ◽  
E. P�ppel
Keyword(s):  
Different Color ◽  
Color Induction ◽  
Color Channels

scholarly journals Color image steganalysis based on channel gradient correlation

2019 ◽  
Vol 15 (5) ◽  
pp. 155014771985203 ◽  
Author(s):  
Yuhan Kang ◽  
Fenlin Liu ◽  
Chunfang Yang ◽  
Lingyun Xiang ◽  
Xiangyang Luo ◽  
...  
Keyword(s):  
Color Image ◽  
Ensemble Classifier ◽  
Image Steganography ◽  
Geometric Transformation ◽  
Image Steganalysis ◽  
Different Color ◽  
Occurrence Matrix ◽  
Color Image Steganography ◽  
The Internet Of Things ◽  
Color Channels

It is one of the potential threats to the Internet of Things to reveal confidential messages by color image steganography. The existing color image steganalysis algorithm based on channel geometric transformation measures owns higher accuracy than the others, but it fails to utilize the correlation between the gradient amplitudes of different color channels. Therefore, this article points out that the color image steganography weakens the correlation between the gradient amplitudes of different color channels and proposes a color image steganalysis algorithm based on channel gradient correlation. The proposed algorithm extracts the co-occurrence matrix feature from the gradient amplitude residuals among different color channels and then combines it with the existing color image steganalysis features to train the ensemble classifier for color image steganalysis. The experimental results show that, for WOW and S-UNIWARD steganography, compared with the existing algorithms, the proposed algorithm outperforms the existing algorithms.

Perceived Glossiness: Beyond Surface Properties

2019 ◽  
Vol 2019 (1) ◽  
pp. 37-42
Author(s):  
Davit Gigilashvili ◽  
Jean-Baptiste Thomas ◽  
Marius Pedersen ◽  
Jon Yngve Hardeberg
Keyword(s):  
Surface Properties ◽  
Human Subjects ◽  
Surface Geometry ◽  
Surface Reflection ◽  
Different Color

Gloss is widely accepted as a surface- and illuminationbased property, both by definition and by means of metrology. However, mechanisms of gloss perception are yet to be fully understood. Potential cues generating gloss perception can be a product of phenomena other than surface reflection and can vary from person to person. While human observers are less likely to be capable of inverting optics, they might also fail predicting the origin of the cues. Therefore, we hypothesize that color and translucency could also impact perceived glossiness. In order to validate our hypothesis, we conducted series of psychophysical experiments asking observers to rank objects by their glossiness. The objects had the identical surface geometry and shape but different color and translucency. The experiments have demonstrated that people do not perceive objects with identical surface equally glossy. Human subjects are usually able to rank objects of identical surface by their glossiness. However, the strategy used for ranking varies across the groups of people.

Variable Precision Depth Encoding for 3D Range Geometry Compression

2020 ◽  
Vol 2020 (17) ◽  
pp. 34-1-34-7
Author(s):  
Matthew G. Finley ◽  
Tyler Bell
Keyword(s):  
Normal Distribution ◽  
Arbitrary Distribution ◽  
File Size ◽  
Geometry Compression ◽  
Variable Precision ◽  
Wide Range ◽  
Novel Method ◽  
Encoding Method ◽  
Rgb Image ◽  
Color Channels

This paper presents a novel method for accurately encoding 3D range geometry within the color channels of a 2D RGB image that allows the encoding frequency—and therefore the encoding precision—to be uniquely determined for each coordinate. The proposed method can thus be used to balance between encoding precision and file size by encoding geometry along a normal distribution; encoding more precisely where the density of data is high and less precisely where the density is low. Alternative distributions may be followed to produce encodings optimized for specific applications. In general, the nature of the proposed encoding method is such that the precision of each point can be freely controlled or derived from an arbitrary distribution, ideally enabling this method for use within a wide range of applications.

scholarly journals A Source of a Different Color: Exploring the Influence of Three Kinds of Science Communication on Audience Attitudes Toward Research

2019 ◽  
Vol 4 ◽  
Author(s):  
Stephanie Tom Tong ◽  
Fred Vultee ◽  
Sean Kolhoff ◽  
Allison B. Elam ◽  
Mostafa Aniss
Keyword(s):  
Science Communication ◽  
Different Color

Virtual Fluorescence Color Channels by Selective Photobleaching in Digital PCR Applied to the Quantification of KRAS Point Mutations

2021 ◽  
Author(s):  
Franziska Schlenker ◽  
Elena Kipf ◽  
Nadine Borst ◽  
Tobias Hutzenlaub ◽  
Roland Zengerle ◽  
...  
Keyword(s):  
Point Mutations ◽  
Digital Pcr ◽  
Fluorescence Color ◽  
Color Channels

scholarly journals The Application of Machine Learning for Cultivar Discrimination of Sweet Cherry Endocarp

Agriculture ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 6
Author(s):  
Ewa Ropelewska
Keyword(s):  
Sweet Cherry ◽  
Color Space ◽  
Geometric Parameters ◽  
Geometric Features ◽  
Color Spaces ◽  
Discriminative Models ◽  
Sweet Cherries ◽  
Rgb Color Space ◽  
Cultivar Discrimination ◽  
Color Channels

The aim of this study was to evaluate the usefulness of the texture and geometric parameters of endocarp (pit) for distinguishing different cultivars of sweet cherries using image analysis. The textures from images converted to color channels and the geometric parameters of the endocarp (pits) of sweet cherry ‘Kordia’, ‘Lapins’, and ‘Büttner’s Red’ were calculated. For the set combining the selected textures from all color channels, the accuracy reached 100% when comparing ‘Kordia’ vs. ‘Lapins’ and ‘Kordia’ vs. ‘Büttner’s Red’ for all classifiers. The pits of ‘Kordia’ and ‘Lapins’, as well as ‘Kordia’ and ‘Büttner’s Red’ were also 100% correctly discriminated for discriminative models built separately for RGB, Lab and XYZ color spaces, G, L and Y color channels and for models combining selected textural and geometric features. For discrimination ‘Lapins’ and ‘Büttner’s Red’ pits, slightly lower accuracies were determined—up to 93% for models built based on textures selected from all color channels, 91% for the RGB color space, 92% for the Lab and XYZ color spaces, 84% for the G and L color channels, 83% for the Y channel, 94% for geometric features, and 96% for combined textural and geometric features.

scholarly journals Application of Fast Non-Local Means Algorithm for Noise Reduction Using Separable Color Channels in Light Microscopy Images

2021 ◽  
Vol 18 (6) ◽  
pp. 2903
Author(s):  
Seong-Hyeon Kang ◽  
Ji-Youn Kim
Keyword(s):  
Light Microscopy ◽  
Noise Reduction ◽  
Natural Image ◽  
Search Window ◽  
Local Means ◽  
Image Characteristics ◽  
Non Local ◽  
Spatial Quality ◽  
Evaluation Parameters ◽  
Color Channels

The purpose of this study is to evaluate the various control parameters of a modeled fast non-local means (FNLM) noise reduction algorithm which can separate color channels in light microscopy (LM) images. To achieve this objective, the tendency of image characteristics with changes in parameters, such as smoothing factors and kernel and search window sizes for the FNLM algorithm, was analyzed. To quantitatively assess image characteristics, the coefficient of variation (COV), blind/referenceless image spatial quality evaluator (BRISQUE), and natural image quality evaluator (NIQE) were employed. When high smoothing factors and large search window sizes were applied, excellent COV and unsatisfactory BRISQUE and NIQE results were obtained. In addition, all three evaluation parameters improved as the kernel size increased. However, the kernel and search window sizes of the FNLM algorithm were shown to be dependent on the image processing time (time resolution). In conclusion, this work has demonstrated that the FNLM algorithm can effectively reduce noise in LM images, and parameter optimization is important to achieve the algorithm’s appropriate application.

Sign in / Sign up

Export Citation Format

Share Document