Real Color Cathodoluminescence (CL) in the SEM: Physics, Color Display and Applications

1990 ◽  
Vol 48 (1) ◽  
pp. 368-369
Author(s):  
G.V. Saparin ◽  
S.K. Obyden
Keyword(s):  
Color Image ◽  
Visible Region ◽  
Color Discrimination ◽  
Total Power ◽  
Color Contrast ◽  
Color Channel ◽  
Commercial Television ◽  
Black And White ◽  
White Counterpart ◽  
Spectral Bands

This paper is concerned with a novel technique of investigating the CL of solids in SEM by means of spectral topographical analysis (use of real color contrast determined by the local CL spectrum).The present-day black-and-white visualizing systems allow images with the number of brightness gradations more than 100. The observer is capable of distinguishing no more than 16 levels of monochrome color (grey levels) at a time. The situation differs when color contrast is used. In the color image, the elements of the same brightness can be discriminated by color contrast. Generally, color image elements can be discriminated both by brightness contrast and by color contrast. For example, only three primary colors (red, green and blue) are employed in commercial television, and the total number of hues approaches 16. If white is used as the reference color, the number of hues amounts to 12000, of which only one third can be displayed by the standard color monitor. The knowledge of color discrimination thresholds allows one to determine the number of colors discernable by eye, this number being about 1300. Thus, color contrast in SEM increases the information content of the image by about two orders, as compared with its black-and-white counterpart. This method of information representation does not practically allow any loss of information in forming the CL image in the visible region. SEM allows the formation of the image in real colors determined by the local CL spectra of the object. The color of the point is determined by the total power of all the detected spectral bands and lines. Thus, the color CL image represents spectral topographical information about the object surface. The signal forming this image for one color channel can be presented as.

scholarly journals Auto-Colorization of Historical Images Using Deep Convolutional Neural Networks

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2258
Author(s):  
Madhab Raj Joshi ◽  
Lewis Nkenyereye ◽  
Gyanendra Prasad Joshi ◽  
S. M. Riazul Islam ◽  
Mohammad Abdullah-Al-Wadud ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
User Study ◽  
Mean Squared Error ◽  
Color Image ◽  
Machine Learning Techniques ◽  
Global Features ◽  
Black And White ◽  
Historical Images ◽  
Learning Techniques

Enhancement of Cultural Heritage such as historical images is very crucial to safeguard the diversity of cultures. Automated colorization of black and white images has been subject to extensive research through computer vision and machine learning techniques. Our research addresses the problem of generating a plausible colored photograph of ancient, historically black, and white images of Nepal using deep learning techniques without direct human intervention. Motivated by the recent success of deep learning techniques in image processing, a feed-forward, deep Convolutional Neural Network (CNN) in combination with Inception- ResnetV2 is being trained by sets of sample images using back-propagation to recognize the pattern in RGB and grayscale values. The trained neural network is then used to predict two a* and b* chroma channels given grayscale, L channel of test images. CNN vividly colorizes images with the help of the fusion layer accounting for local features as well as global features. Two objective functions, namely, Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR), are employed for objective quality assessment between the estimated color image and its ground truth. The model is trained on the dataset created by ourselves with 1.2 K historical images comprised of old and ancient photographs of Nepal, each having 256 × 256 resolution. The loss i.e., MSE, PSNR, and accuracy of the model are found to be 6.08%, 34.65 dB, and 75.23%, respectively. Other than presenting the training results, the public acceptance or subjective validation of the generated images is assessed by means of a user study where the model shows 41.71% of naturalness while evaluating colorization results.

New Set of Invariant Quaternion Krawtchouk Moments for Color Image Representation and Recognition

2021 ◽  
pp. 2250037
Author(s):  
Gaber Hassan ◽  
Khalid M. Hosny ◽  
R. M. Farouk ◽  
Ahmed M. Alzohairy
Keyword(s):  
Quaternion Algebra ◽  
Color Image ◽  
Image Representation ◽  
Color Images ◽  
Color Channel ◽  
Krawtchouk Polynomials ◽  
Krawtchouk Moments ◽  
Similarity Transformations ◽  
The Stability ◽  
Discrete Moments

One of the most often used techniques to represent color images is quaternion algebra. This study introduces the quaternion Krawtchouk moments, QKrMs, as a new set of moments to represent color images. Krawtchouk moments (KrMs) represent one type of discrete moments. QKrMs use traditional Krawtchouk moments of each color channel to describe color images. This new set of moments is defined by using orthogonal polynomials called the Krawtchouk polynomials. The stability against the translation, rotation, and scaling transformations for QKrMs is discussed. The performance of the proposed QKrMs is evaluated against other discrete quaternion moments for image reconstruction capability, toughness against various types of noise, invariance to similarity transformations, color face image recognition, and CPU elapsed times.

scholarly journals Recombination Lasers in the XUV Spectral Region

1984 ◽  
Vol 86 ◽  
pp. 234-240
Author(s):  
G.J. Pert
Keyword(s):  
Transition Probability ◽  
Unit Length ◽  
Energy Levels ◽  
Ultra Violet ◽  
Statistical Weight ◽  
Laser Medium ◽  
Total Power ◽  
Spontaneous Transition ◽  
Spectral Bands ◽  
Conventional Laser

In a conventional laser operating in the near ultra-violet, optical or infra-red spectral bands the photon energies, not exceeding lOeV, are closely matched to the electronic or molecular energy levels of neutral and weakly ionised atoms. Consequently typical photon energies (~ eV), and transition lifetimes (~ ns) closely match the characteristics of fast electrical circuitry feeding a weakly ionised discharge which may be used to pump either directly or indirectly the laser medium.In a X-ray laser operating at about 10Å, photon energies are about 1 keV, and lifetimes about 10−14s (l0fs). In consequence the power required to pump the laser must be expected to increase rapidly as the wavelength decreases. The gain per unit length is given by:where ζ is the line shape factor, A the spontaneous transition probability, λ the wavelength, and Δν the width of the line, and (n2,g2) and (n3,g3) the population density and statistical weight of the lower and upper laser states respectively. The total power loss per unit area, p, of the medium must exceed that emitted by spontaneous decay of the laser transition.

Conformity in the Rat: A Leader's Selection of Door Color versus a Learned Door-Color Discrimination

1977 ◽  
Vol 44 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Robert J. Konopasky ◽  
Gabor A. Telegdy
Keyword(s):  
Color Discrimination ◽  
Black And White ◽  
Y Maze ◽  
Nonhuman Species ◽  
Selection Of

An analogue for studying conformity in nonhuman species was developed. Rats trained to follow a leader, which discriminated between black and white doors in a Y-maze, learned to follow and to discriminate between the black and white doors. When the incorrect or unrewarded door color was selected by substitute leaders, followers conformed on 60% of the trials.

IDENTIFICATION OF CROPLAND AND AREA ESTIMATION FROM AERIAL PHOTOGRAPHY AND SATELLITE IMAGERY

1975 ◽  
Vol 55 (1) ◽  
pp. 221-232 ◽  
Author(s):  
A. R. MACK ◽  
K. E. BOWREN
Keyword(s):  
Aerial Photographs ◽  
Cereal Crops ◽  
Grey Level ◽  
Level Densities ◽  
Black And White ◽  
Spectral Bands ◽  
Grey Scale ◽  
Topographic Survey ◽  
Field Identification ◽  
Red Radiation

The feasibility of using multiband aerial photographs and ERTS-1 imagery for manual field identification and measurements is presented for a Moderately Cold Subhumid Soil Climatic region of Saskatchewan. Using a simple six-step scale criterion, numeric values were assigned to the grey-level densities on black and white photographs (August 1972) for the infrared and red radiation bands. The grey-level densities were calibrated to known crops or other features, determined from data taken on the ground from training sites. A classification key was developed from the calibrated grey-scale values for the two spectral bands. Using the classification key, > 90% of the cereal crops — harvested, cereal crops not harvested, rapeseed, and fallow land — were identified on areas adjacent to the training site. It was not possible in this study to distinguish between wheat and barley from August photography. Nearby sites were used to verify the criteria. For nonnumeric analyses, infrared color was useful to substantiate the results. In general, the green spectral reflection appeared to be similar to the red for most of the fields except for a few of the fallow fields and grassland. However, further studies are required to evaluate the place of the green band in crop identification. The transference of known physiographic features from topographic survey maps and high-altitude aerial photographs onto ERTS imagery facilitated establishment of field boundaries and area measurements. By comparing the values of unknown fields to those calibrated with known features on the same photograph, variation in exposure, photographic development, and reproduction are eliminated.

scholarly journals Seam welds quality control improvement using method of pseudo-color coding images

2021 ◽  
Vol 2094 (2) ◽  
pp. 022058
Author(s):  
M F Noskov
Keyword(s):  
Quality Control ◽  
Color Image ◽  
Color Coding ◽  
Visual Examination ◽  
X Ray ◽  
Black And White ◽  
Optical Mixing ◽  
Pseudo Color ◽  
Ray Methods ◽  
Methods Of Control

Abstract The method of seam welds quality control using X-ray is considered. The X-ray methods of control are based on the capability of gamma radiation to penetrate through a metal including welded areas. Regions having defects - pores, faulty welds, cracks, scale inclusions - look darker on images. Appearance, linear dimensions and depths of the defects usually are determined by a visual examination comparing the X-ray image with standard defects images. It is known that a human eye can distinguish not more than 12-15 shades on a black and white image but more than a hundred on a colored image. The paper considers possibilities of the developed method by the author and based on the optical mixing of two or three complementary colors - red, blue and green. The method can use only one pair of the colors at a time, i.e. it is possible to have three various pairs for a pseudo-color image. The obtained pseudo-color image has the same informational capacity as the original black and white image. But the greater fraction of the saved information becomes available for visual examination of the X-ray image. In the end the efficiency of the seam weld quality control increases.

A Color Contrast Definition for Perceptually Based Color Image Coding

2012 ◽  
Vol 2 (1) ◽  
pp. 33-55
Author(s):  
J. Gutierrez ◽  
G. Camps-Valls ◽  
M.J. Luque ◽  
J. Malo
Keyword(s):  
Image Coding ◽  
Color Image ◽  
Color Contrast ◽  
Color Image Coding

An automatic technique for presentation of coincident‐loop, impulse‐response, transient, electromagnetic data

Geophysics ◽  
1994 ◽  
Vol 59 (10) ◽  
pp. 1542-1550 ◽  
Author(s):  
Richard S. Smith ◽  
R. N. Edwards ◽  
G. Buselli
Keyword(s):  
Color Image ◽  
Synthetic Data ◽  
Depth Image ◽  
Depth Information ◽  
Color Contrast ◽  
Computationally Efficient ◽  
Apparent Conductivity ◽  
Transient Electromagnetic ◽  
Anomalous Feature ◽  
Depth Curves

Coincident‐loop TEM sounding data are often presented by plotting the half‐space apparent conductivity as a function of delay time. A new algorithm generates an improved presentation that plots the apparent conductivity as a function of depth. The resulting data may be further processed to sharpen or “spike” the smoothly varying apparent‐conductivity/depth curves in an attempt to better represent the rapid changes in conductivity that often exist in the earth. The algorithm described involves an approximation, but is simple, easy to use, and computationally efficient. A layered conductivity structure is assumed, so the algorithm is best for areas where the geology is approximately horizontal. However, the algorithm can also be used to identify anomalous features that are not infinite horizontal layers. The spiked conductivity models derived from synthetic data are consistent with the original layered‐earth models and show a greater resolution than the apparent‐conductivity/depth curves, and sometimes amplify noise in the data. When data are collected along a profile line, the conductivity/depth information can be converted to a color image. For profile data collected over the Elura orebody, the image of the spiked conductivity section shows an anomalous feature at the orebody, and the color contrast is more marked than it is on the apparent‐conductivity/depth image.

Sign in / Sign up

Export Citation Format

Share Document