scholarly journals Image Fusion Using a Parameterized Logarithmic Image Processing Framework

Image Fusion ◽  
10.5772/15306 ◽  
2011 ◽  
Author(s):  
Sos S. ◽  
Karen A. ◽  
Shahan C.
Keyword(s):  
Image Processing ◽  
Image Fusion ◽  
Logarithmic Image Processing ◽  
Processing Framework

scholarly journals A Parametric Logarithmic Image Processing Framework Based on Fuzzy Graylevel Accumulation by the Hamacher T-Conorm

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4857
Author(s):  
Constantin Vertan ◽  
Corneliu Florea ◽  
Laura Florea
Keyword(s):  
Image Processing ◽  
Real World ◽  
Digital Images ◽  
Gray Level ◽  
Accumulation Process ◽  
Fuzzy Modelling ◽  
Parameterized Family ◽  
Logarithmic Image Processing ◽  
Suitable Framework ◽  
Processing Framework

It has been proven that Logarithmic Image Processing (LIP) models provide a suitable framework for visualizing and enhancing digital images acquired by various sources. The most visible (although simplified) result of using such a model is that LIP allows the computation of graylevel addition, subtraction and multiplication with scalars within a fixed graylevel range without the use of clipping. It is claimed that a generalized LIP framework (i.e., a parameterized family of LIP models) can be constructed on the basis of the fuzzy modelling of gray level addition as an accumulation process described by the Hamacher conorm. All the existing LIP and LIP-like models are obtained as particular cases of the proposed framework in the range corresponding to real-world digital images.

scholarly journals CHARACTERIZATION OF DIESEL SPRAY IMAGES USING THE LOGARITHMIC IMAGE PROCESSING FRAMEWORK

2011 ◽  
Vol 26 (3) ◽  
pp. 145 ◽  
Author(s):  
Cecile Petit ◽  
Michel Jourlin ◽  
Wolfgang Reckers
Keyword(s):  
Image Processing ◽  
Monochromatic Light ◽  
Internal Symmetry ◽  
Diesel Spray ◽  
Diesel Sprays ◽  
Spray Plume ◽  
Logarithmic Image Processing ◽  
Logarithmic Distance ◽  
Processing Framework ◽  
Spray Characterization

The increasing levels of emission standards in Diesel Engines require a detailed understanding, combustion and after treatment. This paper focuses on the spray development as one key parameter in the mixture preparation. The presentation of a methodology to differentiate the internal symmetry of spray images taken under different environmental conditions is presented. In a first step, a preprocessing is performed, then an image re-centering is made using the logarithmic average, afterwards different symmetry axes based on grey levels or on the plume boundary are calculated and, finally, the logarithmic distance characterizing the spray plume internal symmetry is computed. This distance gives more importance to the high grey level pixels, so using our optical setup, it characterizes the liquid continuous core symmetry. The methodology relies on the logarithmic image processing framework, providing a set of specific algebraic and functional operations to analyze images. This paper is an application of the logarithmic image processing framework on Diesel spray characterization. This is a step further in the quantitative diesel spray characterization by means of image analysis. The presented method can be applied to Diesel sprays illuminated with polychromatic or monochromatic light, under atmospheric or pressurized conditions.

scholarly journals REGION HOMOGENEITY IN THE LOGARITHMIC IMAGE PROCESSING FRAMEWORK: APPLICATION TO REGION GROWING ALGORITHMS

2019 ◽  
Vol 38 (1) ◽  
pp. 43
Author(s):  
Guillaume Noyel ◽  
Michel Jourlin
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
State Of The Art ◽  
Region Growing ◽  
Segmentation Method ◽  
Image Region ◽  
Logarithmic Image Processing ◽  
Image Component ◽  
Processing Framework ◽  
Component Tree

In order to create an image segmentation method robust to lighting changes, two novel homogeneity criteria of an image region were studied. Both were defined using the Logarithmic Image Processing (LIP) framework whose laws model lighting changes. The first criterion estimates the LIP-additive homogeneity and is based on the LIP-additive law. It is theoretically insensitive to lighting changes caused by variations of the camera exposure-time or source intensity. The second, the LIP-multiplicative homogeneity criterion, is based on the LIP-multiplicative law and is insensitive to changes due to variations of the object thickness or opacity. Each criterion is then applied in Revol and Jourlin’s (1997) region growing method which is based on the homogeneity of an image region. The region growing method becomes therefore robust to the lighting changes specific to each criterion. Experiments on simulated and on real images presenting lighting variations prove the robustness of the criteria to those variations. Compared to a state-of the art method based on the image component-tree, ours is more robust. These results open the way to numerous applications where the lighting is uncontrolled or partially controlled.

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 Using Relion software within Scipion framework

2020 ◽  
Author(s):  
Grigory Sharov ◽  
Dustin R. Morado ◽  
Marta Carroni ◽  
José Miguel de la Rosa-Trevín
Keyword(s):  
Image Processing ◽  
User Interfaces ◽  
Published Data ◽  
New Developments ◽  
Processing Pipeline ◽  
Software Packages ◽  
File Formats ◽  
Processing Framework ◽  
Taking Care

Scipion is a modular image processing framework integrating several software packages under a unified interface while taking care of file formats and conversions. Here new developments and capabilities of the Scipion plugin for the Relion software are presented and illustrated with the image processing pipeline of published data. The user interfaces of Scipion and Relion are compared and the key differences highlighted, allowing this manuscript to be used as a guide for both new and experienced users of these software. Different streaming image processing options are also discussed demonstrating the flexibility of the Scipion framework.SynopsisAn overview of the Scipion plugin for the Relion software is presented and various capabilities of image processing within Scipion framework are discussed.

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. 

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