scholarly journals Setting White, Black and Gamma on Continuous Tone Grayscale and Color Images using Photoshop

2003 ◽  
Vol 11 (3) ◽  
pp. 16-19
Author(s):  
Jerry Sedgewick
Keyword(s):  
Digital Images ◽  
Color Images ◽  
Capillary Action ◽  
Dot Gain ◽  
Continuous Tone ◽  
Black Region ◽  
Contrast Range ◽  
Capillary Phenomenon

The contrast range of many digital images needs to be reset before outputting images to various ends. This is especially important when printing to paper because ink absorbs into papers through a capillary action, most in the cheapest papers (such as newspaper) and least in high gloss paper from slick magazines. The capillary phenomenon is known as dot gain In the printing world, since images are redefined as small dots when printing to publications, The result of dot gain is seen most in a loss of details or muddiness in the shadow or the black region of images.

An Algorithmic Approach Based on CMS Edge Detection Technique for the Processing of Digital Images

2020 ◽  
pp. 252-272
Author(s):  
Kalyan Kumar Jena ◽  
Sasmita Mishra ◽  
Sarojananda Mishra
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Images ◽  
Color Images ◽  
Experimental Results ◽  
Detection Technique ◽  
Algorithmic Approach ◽  
Current Scenario ◽  
Edge Detection Method

Research in the field of digital image processing (DIP) has increased in the current scenario. Edge detection of digital images is considered as an important area of research in DIP. Detecting edges in different digital images accurately is a challenging work in DIP. Different methods have been introduced by different researchers to detect the edges of images. However, no method works well under all conditions. In this chapter, an edge detection method is proposed to detect the edges of gray scale and color images. This method focuses on the combination of Canny, mathematical morphological, and Sobel (CMS) edge detection operators. The output of the proposed method is produced using matrix laboratory (MATLAB) R2015b and compared with Sobel, Prewitt, Roberts, Laplacian of Gaussian (LoG), Canny, and mathematical morphological edge detection operators. The experimental results show that the proposed method works better as compared to other existing methods in detecting the edges of images.

scholarly journals Compare the Similarity between Two Quantum Images

2021 ◽  
Author(s):  
You-hang Liu ◽  
Zai-dong Qi ◽  
Qiang Liu
Keyword(s):  
Image Processing ◽  
Digital Images ◽  
Quantum Computer ◽  
Quantum Algorithms ◽  
Color Images ◽  
The Real ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Quantum Images

Abstract Comparing the similarity between digital images is an important subroutine in various image processing algorithms. In this study, we present three quantum algorithms for comparing the similarity between two quantum images. These algorithms apply to binary, grey and color images respectively. Without considering the image preparation, the proposed algorithms achieve exponential acceleration than the existing quantum and classical methods in complexity. At the end of this paper, an experiment based on the real quantum computer of IBMQ and simulations verify the effectiveness of the algorithms.

scholarly journals A Few Thoughts About Image File Storage

2004 ◽  
Vol 12 (1) ◽  
pp. 26-29
Author(s):  
Michael Bode
Keyword(s):  
Digital Images ◽  
Data File ◽  
Color Images ◽  
File Format ◽  
Large Array ◽  
The Core ◽  
Image File ◽  
File Storage ◽  
The Right

A recent thread on the MSA list server about problems with image formats (in this case TIF or TIFF) showed, that there is a bit of confusion in the microscopy community about the best file format for digital images. I will try to shed a bit of light onto this problem.Digital images are at the core a large array of numbers. One number per pixel for b/w images, 3 numbers per pixel for color images. The simplest file format consists of 2 numbers that define the width and height of the image, and then just a listing of numbers for each pixel. By using the right conventions, the image can be recreated from a data file like mis. In essence, this is the format of a bitmap image (BMP), and other formats derived from it.

An Improved Artificial Bee Colony Algorithm for the Object Recognition Problem in Complex Digital Images Using Template Matching

2010 ◽  
Vol 1 (2) ◽  
pp. 54-70 ◽  
Author(s):  
Chidambaram Chidambaram ◽  
Heitor Silvério Lopes
Keyword(s):  
Object Recognition ◽  
Template Matching ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Digital Images ◽  
Color Images ◽  
Recognition Problem ◽  
Reference Image ◽  
Bee Colony ◽  
Collective Foraging

In this paper, the authors present an improved Artificial Bee Colony Algorithm (ABC) for the object recognition problem in complex digital images. The ABC is a new metaheuristics approach inspired by the collective foraging behavior of honey bee swarms. The objective is to find a pattern or reference image (template) of an object somewhere in a target landscape scene that may contain noise and changes in brightness and contrast. First, several search strategies were tested to find the most appropriate. Next, many experiments were done using complex digital grayscale and color images. Results are analyzed and compared with other algorithms through Pareto plots and graphs that show that the improved ABC was more efficient than the original ABC.

What Is a Picture Worth?: Digital Imaging Applications in Autopsy Reports

2004 ◽  
Vol 128 (11) ◽  
pp. 1247-1250
Author(s):  
Bobbi Pritt ◽  
Pamela Gibson ◽  
Kumarasen Cooper ◽  
Nicolas Hardin
Keyword(s):  
Image Quality ◽  
Digital Images ◽  
Mail Survey ◽  
Color Images ◽  
Added Value ◽  
Clinical Impression ◽  
Survey Response Rate ◽  
Autopsy Report ◽  
E Mail ◽  
Microscopic Findings

Abstract Context.—An image-enhanced report (IER) containing color digital images can serve as an educational tool and document important gross and microscopic findings in anatomic pathology. Objective.—To determine the clinical impression of IERs on an academic autopsy service. Design.—Autopsy IERs were initiated at this institution in December 2001. From January 2002 to July 2003, 261 hospital-service autopsies were performed; color images were produced for 39 (15%) of these autopsies. Of these IERs, 29 were distributed to 74 hospital-employed physicians. Each hospital physician recipient was sent a 6-question e-mail survey to evaluate his or her impression of image quality and added value. Results.—Of the 74 hospital-employed physicians sent an IER, 41 responded to the survey (response rate, 55%). Twenty-one respondents recalled receiving a report with color images. Image quality was uniformly rated as good or excellent. Ninety-five percent thought the images increased their understanding of the report, and 76% thought that the images increased the utility of the report. All respondents stated they would (or did) use the images for educational purposes. Twenty-one percent of all respondents thought the presence of color images would increase their likelihood of requesting a future autopsy. Conclusions.—Color digital images are perceived as a valuable addition to the autopsy report. Although clinicians did not consider color images a strong motivator to request a future autopsy, most thought that the images enhanced their understanding and the utility of the report. All respondents stated they would use the images to educate themselves, medical students, residents, and/or the patient's family.

An Improved Artificial Bee Colony Algorithm for the Object Recognition Problem in Complex Digital Images Using Template Matching

2012 ◽  
pp. 141-157 ◽  
Author(s):  
Chidambaram Chidambaram ◽  
Heitor Silvério Lopes
Keyword(s):  
Object Recognition ◽  
Template Matching ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Digital Images ◽  
Color Images ◽  
Recognition Problem ◽  
Reference Image ◽  
Bee Colony ◽  
Collective Foraging

In this paper, the authors present an improved Artificial Bee Colony Algorithm (ABC) for the object recognition problem in complex digital images. The ABC is a new metaheuristics approach inspired by the collective foraging behavior of honey bee swarms. The objective is to find a pattern or reference image (template) of an object somewhere in a target landscape scene that may contain noise and changes in brightness and contrast. First, several search strategies were tested to find the most appropriate. Next, many experiments were done using complex digital grayscale and color images. Results are analyzed and compared with other algorithms through Pareto plots and graphs that show that the improved ABC was more efficient than the original ABC.

scholarly journals The effect of some of spaces and sets of topology on the types of digital images

2021 ◽  
pp. 119-133
Author(s):  
Prof Hindrustum Shaaban ◽  
Alyaa Yousif Khudayir
Keyword(s):  
Digital Images ◽  
Three Dimensional ◽  
Color Images ◽  
Digital Topology ◽  
Two Dimensional ◽  
Matlab Software ◽  
Closed Set ◽  
Opposite Color

There is a growing interest in studying and improving the characteristics of images and objects in the e-commerce environment. Digital topology is concerned with dealing with the properties and features of two-dimensional (2D) or three-dimensional (3D) digital images such as borders, shapes, the intensity of illumination, and other characteristics. This paper aims to introduce and study new classes of fg-disconnected space and compactly fg-closed set, which could impact the brightness and brightness of the internal components of the types of color images, gray and binary. The paper also aims to find the effect of implementing fg-disconnected space and compactly fg-closed set to determine the brightness and brightness of the internal components of the types of color images, gray and binary. Each research plate contains 30 images of each type of image. Ten different images were chosen at the same time to be analyzed and executed using the proposed system based on MATLAB software. The study proved that higher brightness and light will disappear and delete the components of the image of any kind. This aimed to make the image white and opposite color, the greater darkness, and luminescence will make the picture color mysterious and turn to black.

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