Color image maps from black-and-white photographs

1978 ◽  
Author(s):  
Sheila Martin
Keyword(s):  
Color Image ◽  
Black And White

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.

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.

Color Image Display with Black-and-White Film

2020 ◽  
pp. 187-210
Author(s):  
Guo-Guang Mu ◽  
Zhi-Liang Fang ◽  
Xu-Ming Wang ◽  
Yu-Guang Kuang
Keyword(s):  
Color Image ◽  
Image Display ◽  
Black And White ◽  
White Film

scholarly journals Species review of the genus Boreophilia Benick from North America (Coleoptera, Staphylinidae, Aleocharinae, Athetini): Systematics, habitat, and distribution

ZooKeys ◽  
2019 ◽  
Vol 848 ◽  
pp. 57-102 ◽  
Author(s):  
Jan Klimaszewski ◽  
Derek S. Sikes ◽  
Adam Brunke ◽  
Caroline Bourdon
Keyword(s):  
Phylogenetic Analysis ◽  
New Species ◽  
North America ◽  
Color Image ◽  
Dna Barcode ◽  
Valid Species ◽  
Black And White ◽  
Sternite Viii ◽  
First Time ◽  
A New Species

Fourteen species of the genus Boreophilia Benick are now recognized in North America. Boreophiliainsecuta (Eppelsheim), reported by Lohse (1990) from North America, is a misidentification of a new species, which is described here as B.neoinsecuta Klimaszewski, sp. n., and the true B.insecuta (Epp.) does not occur in North America. An additional new species is found in Alaska, and described as B.beringi Klimaszewski & Brunke, sp. n. The following three species are synonymized (second name being valid): Boreophiliaherschelensis Klimaszewski & Godin, 2012, with Boreophiliavega (Fenyes, 1920); Boreophiliamanitobensis Lohse, 1990, with B.caseyi Lohse, 1990; and B.angusticornis (Bernahuer, 1907) with B.subplana (J Sahlberg, 1880), based on study of genital structures and external morphology. Athetagelida J Sahlberg, 1887, and Athetamunsteri Bernhauer, 1902, considered as Boreophilia in recent publications, are transferred to the genus Atheta Thomson, subgenus Dimetrota. Boreostibapiligera (J Sahlberg) is transferred to Boreophilia based on morphology and the results of our phylogenetic analysis. Boreophilianearctica is recorded from Alberta and B.nomensis is recorded from British Columbia for the first time. Each valid species is illustrated by color image of habitus, and black and white images of genitalia and tergite and sternite VIII. A new key to all Nearctic species of the genus is provided. DNA barcode data were available for nine of the 14 species, which we downloaded, analyzed, and used as additional evidence for the taxonomic conclusions reached herein.

scholarly journals IoT Based Image Processing Filters

2021 ◽  
Vol 1 (4) ◽  
pp. 1-13
Author(s):  
Noor Abbas ◽  
Mohamed Ibrahim Shujaa ◽  
Entithaar Mhwes Zghair
Keyword(s):  
Image Processing ◽  
Internet Of Things ◽  
Color Image ◽  
Processing System ◽  
System Generator ◽  
Black And White ◽  
The Common ◽  
Image Processing Algorithms ◽  
Practical Life ◽  
Main Component

Internet of things (IoT) becomes the backbone of the advanced countries and it has a real contribute to exchange the traditional style or way of practical life, even personal life into smart style, with (IoT) technology the life become more and more easy and professional. internet of things achieves various applications coordinate with sensors and standard protocols to apply what is called machine -to- machine connection (M2M), in this paper we will talk more about the concept of (M2M), the main component of internet of things and finally the common protocols that is used in network, in addition to that this work present an IOT operation with processing system using camera for capturing image and Xilinx system generator(XSG)models for designing  image processing algorithms and the result of  the processing is an image with black and white for edge detection and Thresholding models  and gray color image for gray enhancement model.

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 Testing the randomness of shares in color visual cryptography

2021 ◽  
Author(s):  
Leszek J. Chmielewski ◽  
Mariusz Nieniewski ◽  
Arkadiusz Orłowski
Keyword(s):  
Color Image ◽  
Visual Cryptography ◽  
Color Images ◽  
Reconstructed Image ◽  
Original Image ◽  
Numerical Processing ◽  
Human Eye ◽  
Black And White ◽  
Randomness Tests

AbstractThe concept of black-and-white visual cryptography with two truly random shares, previously applied to color images, was improved by mixing the contents of the segments of each coding image and by randomly changing a specified number of black pixels into color ones. This was done in such a way that the changes of the contents of the decoded image were as small as possible. These modifications made the numbers of color pixels in the shares close to balanced, which potentially made it possible for the shares to be truly random. The true randomness was understood as that the data pass the suitably designed randomness tests. The randomness of the shares was tested with the NIST randomness tests. Part of the tests passed successfully, while some failed. The target of coding a color image in truly random shares was approached, but not yet reached. In visual cryptography, the decoding with the unarmed human eye is of primary importance, but besides this, simple numerical processing of the decoded image makes it possible to greatly improve the quality of the reconstructed image, so that it becomes close to that of the dithered original image.

scholarly journals Automatic gray images colorization based on lab color space

2020 ◽  
Vol 18 (3) ◽  
pp. 1501
Author(s):  
Nidhal K. El Abbadi ◽  
Eman Saleem Razaq
Keyword(s):  
Color Image ◽  
Color Space ◽  
Accurate Method ◽  
Reference Image ◽  
The Public ◽  
Gray Image ◽  
Black And White ◽  
Manual Intervention ◽  
Lab Color Space ◽  
Fully Automatic

<p>The colorization aim to transform a black and white image to a color image. This is a very hard  issue and usually requiring manual intervention by the user to produce high-quality images free of artifact. The public problem of inserting gradients color to a gray image has no accurate method. The proposed method is fully automatic method. We suggested to use reference color image to help transfer colors from reference image to gray image.  The reference image converted to  Lab color space, while the gray scale image normalized according to the lightness channel L. the gray image concatenate with both a, and b channels before converting to RGB image. The results were promised compared with other methods.</p>

scholarly journals IoT Based Image Processing Filters

2021 ◽  
Vol 2 (4) ◽  
pp. 1-13
Author(s):  
Noor Abbas ◽  
Mohamed Ibrahim Shujaa ◽  
Entithaar Mhwes Zghair
Keyword(s):  
Image Processing ◽  
Internet Of Things ◽  
Color Image ◽  
Processing System ◽  
System Generator ◽  
Black And White ◽  
The Common ◽  
Image Processing Algorithms ◽  
Practical Life ◽  
Main Component

Internet of things (IoT) becomes the backbone of the advanced countries and it has a real contribute to exchange the traditional style or way of practical life, even personal life into smart style, with (IoT) technology the life become more and more easy and professional. internet of things achieves various applications coordinate with sensors and standard protocols to apply what is called machine -to- machine connection (M2M), in this paper we will talk more about the concept of (M2M), the main component of internet of things and finally the common protocols that is used in network, in addition to that this work present an IOT operation with processing system using camera for capturing image and Xilinx system generator(XSG)models for designing  image processing algorithms and the result of  the processing is an image with black and white for edge detection and Thresholding models  and gray color image for gray enhancement model.

Analysis and modification of graphic data compression algorithms

2020 ◽  
Vol 25 (4) ◽  
pp. 32-40
Author(s):  
Bouza M.K. ◽  
Keyword(s):  
Color Image ◽  
Jpeg 2000 ◽  
Black And White ◽  
Advantages And Disadvantages ◽  
Graphic Data ◽  
Full Color ◽  
Wide Range ◽  
Site Design ◽  
Lzw Algorithm

The article examines the algorithms for JPEG and JPEG-2000 compression of various graphic images. The main steps of the operation of both algorithms are given, their advantages and disadvantages are noted. The main differences between JPEG and JPEG-2000 are analyzed. It is noted that the JPEG-2000 algorithm allows re-moving visually unpleasant effects. This makes it possible to highlight important areas of the image and improve the quality of their compression. The features of each step of the algorithms are considered and the difficulties of their implementation are compared. The effectiveness of each algorithm is demonstrated by the example of a full-color image of the BSU emblem. The obtained compression ratios were obtained and shown in the corresponding tables using both algorithms. Compression ratios are obtained for a wide range of quality values from 1 to ten. We studied various types of images: black and white, business graphics, indexed and full color. A modified LZW-Lempel-Ziv-Welch algorithm is presented, which is applicable to compress a variety of information from text to images. The modification is based on limiting the graphic file to 256 colors. This made it possible to index the color with one byte instead of three. The efficiency of this modification grows with increasing image sizes. The modified LZW-algorithm can be adapted to any image from single-color to full-color. The prepared tests were indexed to the required number of colors in the images using the FastStone Image Viewer program. For each image, seven copies were obtained, containing 4, 8, 16, 32, 64, 128 and 256 colors, respectively. Testing results showed that the modified version of the LZW algorithm allows for an average of twice the compression ratio. However, in a class of full-color images, both algorithms showed the same results. The developed modification of the LZW algorithm can be successfully applied in the field of site design, especially in the case of so-called flat design. The comparative characteristics of the basic and modified methods are presented.

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