scholarly journals Functional Asplund metrics for pattern matching, robust to variable lighting conditions

2020 ◽  
Author(s):  
Guillaume Noyel ◽  
Michel Jourlin
Keyword(s):  
Image Processing ◽  
Pattern Matching ◽  
Mathematical Morphology ◽  
Exposure Time ◽  
Low Contrast ◽  
Lighting Conditions ◽  
Logarithmic Image Processing ◽  
Robust To Noise ◽  
Complete Framework ◽  
Functional Metrics

In this paper, we propose a complete framework to process images captured under uncontrolled lighting and especially under low lighting. By taking advantage of the Logarithmic Image Processing (LIP) context, we study two novel functional metrics: i) the LIP-multiplicative Asplund metric which is robust to object absorption variations and ii) the LIP-additive Asplund metric which is robust to variations of source intensity or camera exposure-time. We introduce robust to noise versions of these metrics. We demonstrate that the maps of their corresponding distances between an image and a reference template are linked to Mathematical Morphology. This facilitates their implementation. We assess  them in various situations with different lightings and movement. Results show that those maps of distances are robust to lighting variations. Importantly, they are efficient to detect patterns in low-contrast images with a template acquired under a different lighting.

scholarly journals Extending Camera’s Capabilities in Low Light Conditions Based on LIP Enhancement Coupled with CNN Denoising

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7906
Author(s):  
Maxime Carré ◽  
Michel Jourlin
Keyword(s):  
Exposure Time ◽  
Visual Image ◽  
Light Conditions ◽  
Low Light ◽  
Lighting Conditions ◽  
Correct Information ◽  
Logarithmic Image Processing ◽  
Precise Simulation ◽  
Color Preservation

Using a sensor in variable lighting conditions, especially very low-light conditions, requires the application of image enhancement followed by denoising to retrieve correct information. The limits of such a process are explored in the present paper, with the objective of preserving the quality of enhanced images. The LIP (Logarithmic Image Processing) framework was initially created to process images acquired in transmission. The compatibility of this framework with the human visual system makes possible its application to images acquired in reflection. Previous works have established the ability of the LIP laws to perform a precise simulation of exposure time variation. Such a simulation permits the enhancement of low-light images, but a denoising step is required, realized by using a CNN (Convolutional Neural Network). A main contribution of the paper consists of using rigorous tools (metrics) to estimate the enhancement reliability in terms of noise reduction, visual image quality, and color preservation. Thanks to these tools, it has been established that the standard exposure time can be significantly reduced, which considerably enlarges the use of a given sensor. Moreover, the contribution of the LIP enhancement and denoising step are evaluated separately.

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

FPN Analysis and Processing of the Science Grade CCD Alta U9000

2011 ◽  
Vol 301-303 ◽  
pp. 1007-1010
Author(s):  
Yu Lei Yuan ◽  
Ya Bo Luo ◽  
Chao Zhang ◽  
Yong Xing Zhu
Keyword(s):  
Image Processing ◽  
Exposure Time ◽  
The Relationship

The FPN is an important part in CCD noise. The positions of the FPN in CCD are fixed, and the magnitude follows some rules. Through measuring the positions and magnitude of the FPN beforehand, we could eliminate the FPN in the image processing afterward. The causes and forms of the FPN are analyzed. The FPN of the science grad CCD Alta U9000 is introduced. The relationship between the FPN of U9000 and the exposure time is determined with the shutter closed. And the FPN of images taken in another experiment is eliminated. The experiment results well.

scholarly journals Improving Image Quality and Reducing Drift Problems via Automated Data Acquisition and Averaging in a Cs-Corrected TEM

2008 ◽  
Vol 16 (6) ◽  
pp. 36-39 ◽  
Author(s):  
E. Voelkl ◽  
B. Jiang ◽  
Z.R. Dai ◽  
J.P Bradley
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Data Acquisition ◽  
Information Content ◽  
Exposure Time ◽  
Image Acquisition ◽  
Ccd Camera ◽  
Automated Data Acquisition ◽  
Processing Steps

Image acquisition with a CCD camera is a single-press-button activity: after selecting exposure time and adjusting illumination, a button is pressed and the acquired image is perceived as the final, unmodified proof of what was seen in the microscope. Thus it is generally assumed that the image processing steps of e.g., “darkcurrent correction” and “gain normalization” do not alter the information content of the image, but rather eliminate unwanted artifacts.

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