Infrared Electric Image Enhancement Based On Fuzzy Renyi Entropy and Quantum Genetic Algorithm

2011 ◽  
Vol 66-68 ◽  
pp. 1774-1780
Author(s):  
Song Hai Fan ◽  
Shu Hong Yang ◽  
Pu He ◽  
Hong Yu Nie
Keyword(s):  
Genetic Algorithm ◽  
Infrared Image ◽  
Renyi Entropy ◽  
Rényi Entropy ◽  
Maximal Entropy ◽  
Infrared Images ◽  
Low Contrast ◽  
Quantum Genetic Algorithm ◽  
Entropy Principle ◽  
Electric Equipment

Infrared thermograph has been applied in electric equipment inspection widely, but the visual effects of infrared images are always undesirable. Considering the limitation of low luminance，low contrast in infrared images，an enhancement method based on fuzzy Renyi entropy and quantum genetic algorithm is presented in this paper．Firstly，the contrast-sketching function presented in [1] is improved based on the idea of segmentation. Then, in order to segment the infrared image, Renyi entropy is extend to fuzzy domain considering the fuzzy nature of infrared image, and is employed to threshold the infrared image following maximal entropy principle. In order to meet the real-time demand of online monitoring, quantum genetic algorithm is employed to search the optimal parameters of the transform function. The experimental results indicate that the method can well improve the visual effect of infrared electric images．

scholarly journals Dynamics of non-stationary processes that follow the maximum of the Rényi entropy principle

2016 ◽  
Vol 472 (2185) ◽  
pp. 20150324 ◽  
Author(s):  
Dmitry S. Shalymov ◽  
Alexander L. Fradkov
Keyword(s):  
Limit Distribution ◽  
Mass Conservation ◽  
Random Variable ◽  
Renyi Entropy ◽  
Rényi Entropy ◽  
Stationary Processes ◽  
Entropy Principle ◽  
Gradient Principle ◽  
Probability Density Function Pdf ◽  
Speed Gradient

We propose dynamics equations which describe the behaviour of non-stationary processes that follow the maximum Rényi entropy principle. The equations are derived on the basis of the speed-gradient principle originated in the control theory. The maximum of the Rényi entropy principle is analysed for discrete and continuous cases, and both a discrete random variable and probability density function (PDF) are used. We consider mass conservation and energy conservation constraints and demonstrate the uniqueness of the limit distribution and asymptotic convergence of the PDF for both cases. The coincidence of the limit distribution of the proposed equations with the Rényi distribution is examined.

scholarly journals Entropy and Contrast Enhancement of Infrared Thermal Images Using the Multiscale Top-Hat Transform

Entropy ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 244 ◽  
Author(s):  
Julio Mello Román ◽  
José Vázquez Noguera ◽  
Horacio Legal-Ayala ◽  
Diego Pinto-Roa ◽  
Santiago Gomez-Guerrero ◽  
...  
Keyword(s):  
Multiple Scales ◽  
Infrared Image ◽  
Infrared Images ◽  
Public Database ◽  
Human Visual Perception ◽  
Multiple Features ◽  
Thermal Images ◽  
Low Contrast ◽  
Database Evaluation ◽  
Infrared Thermal Images

Discrete entropy is used to measure the content of an image, where a higher value indicates an image with richer details. Infrared images are capable of revealing important hidden targets. The disadvantage of this type of image is that their low contrast and level of detail are not consistent with human visual perception. These problems can be caused by variations of the environment or by limitations of the cameras that capture the images. In this work we propose a method that improves the details of infrared images, increasing their entropy, preserving their natural appearance, and enhancing contrast. The proposed method extracts multiple features of brightness and darkness from the infrared image. This is done by means of the multiscale top-hat transform. To improve the infrared image, multiple scales are added to the bright areas and multiple areas of darkness are subtracted. The method was tested with 450 infrared thermal images from a public database. Evaluation of the experimental results shows that the proposed method improves the details of the image by increasing entropy, also preserving natural appearance and enhancing the contrast of infrared thermal images.

scholarly journals MSIS: Multispectral Instance Segmentation Method for Power Equipment

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Jun Shu ◽  
Juncheng He ◽  
Ling Li
Keyword(s):  
Feature Extraction ◽  
Fault Detection ◽  
Feature Fusion ◽  
Infrared Image ◽  
Current Method ◽  
Power Equipment ◽  
Infrared Images ◽  
Low Contrast ◽  
Novel Structure ◽  
Instance Segmentation

Infrared image of power equipment is widely used in power equipment fault detection, and segmentation of infrared images is an important step in power equipment thermal fault detection. Nevertheless, since the overlap of the equipment, the complex background, and the low contrast of the infrared image, the current method still cannot complete the detection and segmentation of the power equipment well. To better segment the power equipment in the infrared image, in this paper, a multispectral instance segmentation (MSIS) based on SOLOv2 is designed, which is an end-to-end and single-stage network. First, we provide a novel structure of multispectral feature extraction, which can simultaneously obtain rich features in visible images and infrared images. Secondly, a module of feature fusion (MARFN) has been constructed to fully obtain fusion features. Finally, the combination of multispectral feature extraction, the module of feature fusion (MARFN), and instance segmentation (SOLOv2) realize multispectral instance segmentation of power equipment. The experimental results show that the proposed MSIS model has an excellent performance in the instance segmentation of power equipment. The MSIS based on ResNet-50 has 40.06% AP.

The Research of Non-Uniformity Correction of Infrared Image in Thermal Wave Testing Based on Homomorphism Technology

2011 ◽  
Vol 58-60 ◽  
pp. 2376-2380
Author(s):  
Yuan Jia Song ◽  
Wei Zhang ◽  
Zheng Wei Yang ◽  
Guo Feng Jin
Keyword(s):  
Thermal Wave ◽  
Signal To Noise Ratio ◽  
Infrared Image ◽  
Future Research ◽  
Infrared Images ◽  
Signal To Noise ◽  
Improve Image Quality ◽  
High Noise ◽  
Low Contrast ◽  
Homomorphic Filtering

The infrared thermal wave technology is a new nondestructive testing (NDT) method with a kind of advantage, including non-contact, intuitionistic, fast et al. But the infrared images always have defects that the low-contrast and high-noise due to uneven brightness and calefaction in the testing process, which enhance the difficulty of following quantitative distinguishment of defects. Therefore, the improved homomorphic filtering is given in this article. The detailed processes of the method and testing results are given. The results of the experiments show that the method has higher peak signal to noise ratio (PSNR), can improve image quality, which establish basis for future research of image segmentation.

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