An Entropy Interpretation of the Logarithmic Image Processing Model With Application to Contrast Enhancement

2009 ◽  
Vol 18 (5) ◽  
pp. 1135-1140 ◽  
Author(s):  
Guang Deng
Keyword(s):  
Image Processing ◽  
Contrast Enhancement ◽  
Logarithmic Image Processing

Improving focus measurements using logarithmic image processing

2010 ◽  
Vol 242 (3) ◽  
pp. 228-241 ◽  
Author(s):  
M. FERNANDES ◽  
Y. GAVET ◽  
J.-C. PINOLI
Keyword(s):  
Image Processing ◽  
Logarithmic Image Processing

Formulation of Fractional Derivative-Based De-Hazing Algorithm and Implementation on Mobile-Embedded Devices

2019 ◽  
Vol 19 (01) ◽  
pp. 1950003
Author(s):  
Uche A. Nnolim
Keyword(s):  
Image Processing ◽  
Fractional Derivative ◽  
Mobile Devices ◽  
Fractional Order ◽  
Spatial Filter ◽  
Embedded Devices ◽  
Processing Application ◽  
Fractional Order Calculus ◽  
Image Processing Application ◽  
Logarithmic Image Processing

This paper presents the modification of a previously developed algorithm using fractional order calculus and its implementation on mobile-embedded devices such as smartphones. The system performs enhancement on three categories of images such as those exhibiting uneven illumination, faded features/colors and hazy appearance. The key contributions include the simplified scheme for illumination correction, contrast enhancement and de-hazing using fractional derivative-based spatial filter kernels. These are achieved without resorting to logarithmic image processing, histogram-based statistics and complex de-hazing techniques employed by conventional algorithms. The simplified structure enables ease of implementation of the algorithm on mobile devices as an image processing application. Results indicate that the fractional order version of the algorithm yields good results relative to the integer order version and other algorithms from the literature.

scholarly journals Digital Image Processing and Data Retrieval : The Needs

1982 ◽  
Vol 64 ◽  
pp. 109-110
Author(s):  
A. Bijaoui
Keyword(s):  
Image Processing ◽  
Information Extraction ◽  
Noise Reduction ◽  
Contrast Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Data Retrieval

During the last decenny, Digital Image Processing (D.I.P.) has been introduced in astronomical studies to allow the information extraction.In a first step, D.I.P. has been used essentially to provide enhanced images (noise reduction, deconvolution, contrast enhancement), to reduce geometrical or photometrical distorsions and to extract rough data. So, a few reference date are needed (some comparison lines for example).

scholarly journals Image Processing and Scientific Misconduct

1998 ◽  
Vol 6 (4) ◽  
pp. 12-13 ◽  
Author(s):  
William R. Oliver
Keyword(s):  
Image Processing ◽  
Contrast Enhancement ◽  
Scientific Misconduct ◽  
Image Interpretation ◽  
Computer Scientist ◽  
Bodily Injury ◽  
Microscopy Image ◽  
Everyday Work ◽  
Enhancement Method ◽  
Group A

In a recent microscopy discussion group, a correspondent questioned the use of a contrast enhancement method applied to a microscopy image for publication. What kinds of image processing, folk asked, are “acceptable” in a general sense? What kinds of image processing should be noted in the text or caption and what kind of images should be archived?It is an interesting set of questions, and I face them wearing three hats, I am a forensic pathologist who performs forensic image interpretation in the investigation of homicide and assault, an anatomic pathologist with an interest in confocal microscopy, and a computer scientist with training in image processing and computer vision. Image processing is part and parcel of my everyday work. I use tools such as contrast enhancement, debarring, and photogrammetry for image interpretation. I build tools for visualization in my confocal work. I collaborate in the design of data acquisition devices for the evaluation of crime scenes and bodily injury.

Multiple Blind Watermark Algorithm Based on Wavelet Packet Transform and Two-Dimensional Chaos Scramble

2012 ◽  
Vol 532-533 ◽  
pp. 1846-1850 ◽  
Author(s):  
Tian Zhong Zhao ◽  
Tao Chen ◽  
Jia Xu ◽  
Tao Wang ◽  
Wei Yi Shi
Keyword(s):  
Image Processing ◽  
Contrast Enhancement ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Experimental Results ◽  
Two Dimensional ◽  
Hidden Information ◽  
Image Contrast Enhancement ◽  
Multiple Watermarks ◽  
Watermark Algorithm

In this paper, multiple blind watermark algorithm based on wavelet packet transform (WPT) and two-dimensional chaos image scramble is put forward. In the sub-images of WPT, multiple watermarks are embedded and distilled blindly. Meantime, the image contrast enhancement to hidden information before hand can improve its robustness effectively. In order to improve the security, two-dimensional chaos image scramble algorithm is designed. Experimental results show that the multiple blind watermark algorithm has good invisibleness, security and robustness to common image processing and noise attack.

Contrast enhancement of mammogram by image processing

1993 ◽  
Author(s):  
Ying Xiong ◽  
Chan F. Lam ◽  
G. D. Frey ◽  
Marilyn R. Croley
Keyword(s):  
Image Processing ◽  
Contrast Enhancement
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