scholarly journals Multiresolution Decomposition Schemes Using the Parameterized Logarithmic Image Processing Model with Application to Image Fusion

2010 ◽  
Vol 2011 (1) ◽  
Author(s):  
Shahan C. Nercessian ◽  
Karen A. Panetta ◽  
Sos S. Agaian
Keyword(s):  
Image Processing ◽  
Image Fusion ◽  
Multiresolution Decomposition ◽  
Logarithmic Image Processing ◽  
Decomposition Schemes

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

scholarly journals Satellite Image Registration and Image Fusion by using Principle Component Analysis

2018 ◽  
Vol 7 (2.19) ◽  
pp. 106
Author(s):  
Gandla Maharnisha ◽  
Gandla Roopesh Kumar ◽  
R Arunraj
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Image Fusion ◽  
Digital Image Processing ◽  
Spatial Resolution ◽  
Digital Image ◽  
Principle Component Analysis ◽  
Component Analysis ◽  
Principle Component ◽  
Spectral Degradation

This aims to fused image registration and image fusion used to spatial resolution images by principle component analysis method. Digital image processing requires either the full image or a part of image. It will be processed from the user’s point of view like the radius of object. Wavelet technique will improve the spatial resolution to produce spectral degradation in output image. To overcome the spectral degradation, PCA fusion method can be used. PCA uses curve which represent edges and extraction of the detailed information from the image.PAN and MS images are used by individual acquired low frequency approximate component and high frequency detail components in this PCA. To evaluate the image fusion accuracy, Peak Signal to Noise Ratio and Root Mean Square Error are used. The advantages of using digital image processing are preservation of original data accuracy, flexibility and repeatability. 

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.

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