Image Enhancing on Consumer's Displays for Increased Printing

2012 ◽  
Vol 2012 (1) ◽  
pp. 1-6
Author(s):  
Ron Kubara
Keyword(s):  
Image Enhancing

Exploring the harms arising from polysubstance use among performance and image enhancing drug users among young Australian men

2021 ◽  
pp. 100197
Author(s):  
Timothy M Piatkowski ◽  
Matthew Dunn ◽  
Katherine M White ◽  
Leanne M Hides ◽  
Patricia L Obst
Keyword(s):  
Drug Users ◽  
Polysubstance Use ◽  
Image Enhancing

Digital Fractional Order Savitzky-Golay Differentiator and Its Application

2011 ◽  
Author(s):  
Dali Chen ◽  
Dingyu Xue ◽  
YangQuan Chen
Keyword(s):  
Fractional Order ◽  
Least Square ◽  
One Dimension ◽  
Order Derivative ◽  
Noisy Signal ◽  
Fractional Order Derivative ◽  
Least Square Fitting ◽  
Image Enhancing ◽  
The One ◽  
Derivatives Of

Firstly the one-dimension digital fractional order Savitzky-Golay differentiator (1-D DFOSGD), which generalizes the Savitzky-Golay filter from the integer order to the fractional order, is proposed to estimate the fractional order derivative of the noisy signal. The polynomial least square fitting technology and the Riemann-Liouville fractional order derivative definition are used to ensure robust and accuracy. Experiments demonstrate that 1-D DFOSGD can estimate the fractional order derivatives of both ideal signal and noisy signal accurately. Secondly, the two-dimension DFOSGD is obtained from 1-D DFOSGD by defining a group of direction operators, and a new image enhancing method based on 2-D DFOSGD is presented. Experiments demonstrate that 2-D DFOSGD has very good performance on image enhancement.

Method of image enhancing based on shape feature of target

2007 ◽  
Author(s):  
Wei Wu ◽  
Lan Xiang ◽  
Zude Zhou
Keyword(s):  
Shape Feature ◽  
Image Enhancing

scholarly journals The supply of steroids and other performance and image enhancing drugs (PIEDs) in one English city: Fakes, counterfeits, supplier trust, common beliefs and access

2014 ◽  
Vol 3 (3-4) ◽  
pp. 135-144 ◽  
Author(s):  
Ross Coomber ◽  
Adele Pavlidis ◽  
Gisella Hanley Santos ◽  
Michael Wilde ◽  
Wiebke Schmidt ◽  
...  
Keyword(s):  
Image Enhancing

Image Contrast Enhancement Algorithm Based on GM(1,1) and Power Exponential Dynamic Decision

2017 ◽  
Vol 32 (02) ◽  
pp. 1854002 ◽  
Author(s):  
Gang Li
Keyword(s):  
Image Enhancement ◽  
Local Contrast ◽  
Local Enhancement ◽  
Contrast Level ◽  
Image Edge Detection ◽  
Image Contrast Enhancement ◽  
Image Edge ◽  
Image Enhancing ◽  
Enhancement Algorithm

Image enhancement processing is a very important operation during image preprocessing. Compared with to enhancc the overall contrast level of image, enhancing the local contrast of image can improve the level of such contrast directly as well as the quality and effect of image enhancement. In this paper, the gray prediction model is applied to the process of enhancing image local contrast, so as to measure the change range of image local contrast and adaptively adjust the scale of enhancing image local contrast. The simulation results show that, in addition to enhancing the contrast of gray level on the edge of image, the proposed algorithm can inhibit roughened nonedge region and improve the quality of local enhancement processing, which create a more favorable condition for the further image edge detection.

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