New Enhancement Algorithm of Infrared Images Based on Dual Threshold of the Exponential Transform

2014 ◽  
Vol 989-994 ◽  
pp. 3893-3897
Author(s):  
Jing Lv ◽  
Jian Lv ◽  
Chuan Fu Wu ◽  
Yun Zhou ◽  
Feng Pei Sun ◽  
...  
Keyword(s):  
Visible Light ◽  
Imaging System ◽  
Median Filter ◽  
Infrared Image ◽  
Human Vision ◽  
Infrared Images ◽  
Threshold Method ◽  
Exponential Transform ◽  
Detail Image ◽  
Enhancement Algorithm

Since the thermal imaging system detection ability and spatial resolution is lower than visible light CCD array,the definition of the infrared image is lower than that of the visible light image, which needs enhancement to improve image quality and for human vision. This paper proposes an enhancement algorithm of infrared images based on dual threshold of the exponential transform, firstly the original image can be processed by median filter to reduce noise,next separate the detail information of the 14-bit infrared image after noise reduction; then deal the detail image with the double threshold method based on the exponential transform,retaining or enhancing the detail information;when it comes to the base image,deal it with the gray linear mapping method, compressing its dynamic range.Finally the detail image and the base image are composed together after processing,getting 8-bit infrared image which can display and be processed on an ordinary display.

Anti-Alteration Technology for License Plate Recognition System

2011 ◽  
Vol 211-212 ◽  
pp. 156-160
Author(s):  
Xing Yang ◽  
Yong Shun Ling ◽  
Xiao Li Hao ◽  
Hua Yang ◽  
Peng Ma
Keyword(s):  
Visible Light ◽  
Near Infrared ◽  
Imaging System ◽  
Recognition System ◽  
Infrared Range ◽  
License Plate ◽  
Uniform Field ◽  
License Plate Recognition ◽  
Infrared Images ◽  
Field Imaging

In order to realize anti-alteration function for License Plate Recognition System (LPRS), a uniform-field imaging system is designed and a corresponding anti-alteration algorithm is proposed. First, reflection characteristics of license plate and typical alteration material are measured. As a result, the two characteristics in near-infrared range fluctuate moderately and the former is notably lower than the latter. Then the uniform-field imaging system for visible-light and near-infrared is designed to capture the difference above effectively. Finally, the anti-alteration algorithm, composed of license plate location, character matching segmentation and alteration recognition, is introduced. Experimental results have indicated that visible-light and near-infrared images can be acquired stably by the proposed system under the condition of natural illumination and there are discriminable gray differences between license plate and alteration material in near-infrared images; and that success rate and average executive time of the algorithm are 86.5% and 157ms respectively.

A New Method for Improving Infrared Image Quality and its System Implementation

2011 ◽  
Vol 130-134 ◽  
pp. 2989-2992
Author(s):  
Zhan Hua Huan ◽  
He Meng Yang ◽  
Meng Zhu
Keyword(s):  
Polynomial Interpolation ◽  
Imaging System ◽  
Signal To Noise Ratio ◽  
Infrared Image ◽  
Adaptive Threshold ◽  
High Signal ◽  
Piecewise Polynomial ◽  
Correction Algorithm ◽  
Enhancement Method ◽  
Enhancement Algorithm

To obtain high-quality infrared image real-timely, a new correction enhancement method is proposed. The method can both compensate nonuniformity of IRFPA by using calibration-based piecewise polynomial interpolation correction algorithm and increase image contrast by using histogram-based adaptive threshold image enhancement algorithm. The experiment is performed by carrying out the method in an embedded imaging system. The results show that the system can process infrared image real-timely and the processed image is clear with high signal to noise ratio.

scholarly journals Fusion algorithm of visible and infrared image based on anisotropic diffusion and image enhancement (capitalize only the first word in a title (or heading), the first word in a subtitle (or subheading), and any proper nouns)

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0245563
Author(s):  
Hui Huang ◽  
Linlu Dong ◽  
Zhishuang Xue ◽  
Xiaofang Liu ◽  
Caijian Hua
Keyword(s):  
Image Enhancement ◽  
Anisotropic Diffusion ◽  
Infrared Image ◽  
Source Image ◽  
Laplacian Pyramid ◽  
Infrared Images ◽  
Fusion Algorithm ◽  
Public Data ◽  
Visible Images ◽  
Enhancement Algorithm

Aiming at the situation that the existing visible and infrared images fusion algorithms only focus on highlighting infrared targets and neglect the performance of image details, and cannot take into account the characteristics of infrared and visible images, this paper proposes an image enhancement fusion algorithm combining Karhunen-Loeve transform and Laplacian pyramid fusion. The detail layer of the source image is obtained by anisotropic diffusion to get more abundant texture information. The infrared images adopt adaptive histogram partition and brightness correction enhancement algorithm to highlight thermal radiation targets. A novel power function enhancement algorithm that simulates illumination is proposed for visible images to improve the contrast of visible images and facilitate human observation. In order to improve the fusion quality of images, the source image and the enhanced images are transformed by Karhunen-Loeve to form new visible and infrared images. Laplacian pyramid fusion is performed on the new visible and infrared images, and superimposed with the detail layer images to obtain the fusion result. Experimental results show that the method in this paper is superior to several representative image fusion algorithms in subjective visual effects on public data sets. In terms of objective evaluation, the fusion result performed well on the 8 evaluation indicators, and its own quality was high.

A New High-Dynamic-Range Compression and Detail Enhancement Algorithm for Infrared Images

2013 ◽  
Vol 427-429 ◽  
pp. 1813-1816 ◽  
Author(s):  
Ting Ting Liu ◽  
Ya Dong Jiang ◽  
Wei Yi Ding ◽  
Xiang Sheng Meng ◽  
Xian Wang
Keyword(s):  
Dynamic Range ◽  
Infrared Image ◽  
High Dynamic Range ◽  
Linear Mapping ◽  
Infrared Images ◽  
Base Component ◽  
Dynamic Range Compression ◽  
High Dynamic ◽  
Detail Enhancement ◽  
Enhancement Algorithm

Infrared images have the high dynamic range characteristic, generally digitized to 14 bit. While most display devices can only show 8 bit images, so high bit-wide infrared image signal should be compressed to low bit-wide display data without losing the important detail information. A new high-dynamic-range compression and detail enhancement algorithm for infrared images is presented in this paper. In the proposed algorithm, the original infrared image is separated into the low-frequency base component and the high-frequency detail component. Then the base component is compressed with the simple gray level linear mapping, and the detail component is enhanced with the S-curve transformation. Finally, the two components are combined to get the 8 bit enhanced image. The experimental results show that the proposed algorithm can achieve the dynamic range compression while effectively preserve and enhance the local detail information.

Comparative Analysis of Image Measurement Accuracy in High Temperature Based on Visible and Infrared Vision

2013 ◽  
Vol 300-301 ◽  
pp. 1681-1686
Author(s):  
Zheng Liu ◽  
Su Mei Cui ◽  
He Yin ◽  
Yu Chi Lin
Keyword(s):  
High Temperature ◽  
Visible Light ◽  
Measurement Errors ◽  
Measurement Accuracy ◽  
Infrared Image ◽  
Infrared Images ◽  
Image Measurement ◽  
Light Image ◽  
Visible Light Imaging ◽  
Infrared Vision

Image measurement is a common and non-contact dimensional measurement method. However, because of light deflection, visible light imaging is influenced largely, which makes the measurement accuracy reduce greatly. Various factors of visual measurement in high temperature are analyzed with the application of Planck theory. Thereafter, by means of the light dispersion theory, image measurement errors of visible and infrared images in high temperature which caused by light deviation are comparatively analyzed. Imaging errors of visible and infrared images are proposed quantitatively with experiments. Experimental results indicate that, based on the same imaging resolution, the relative error value of visible light image is 3.846 times larger than infrared image in 900°C high temperature. Therefore, the infrared image measurement has higher accuracy than the visible light image measurement in high temperature circumstances.

Reflection interference removal for infrared thermography images based on GAN

2021 ◽  
Vol 63 (9) ◽  
pp. 529-533
Author(s):  
Jiali Zhang ◽  
Yupeng Tian ◽  
LiPing Ren ◽  
Jiaheng Cheng ◽  
JinChen Shi
Keyword(s):  
Neural Networks ◽  
Infrared Thermography ◽  
Metal Surfaces ◽  
Infrared Image ◽  
Infrared Camera ◽  
Infrared Images ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Continuous Application ◽  
Visible Images

Reflection in images is common and the removal of complex noise such as image reflection is still being explored. The problem is difficult and ill-posed, not only because there is no mixing function but also because there are no constraints in the output space (the processed image). When it comes to detecting defects on metal surfaces using infrared thermography, reflection from smooth metal surfaces can easily affect the final detection results. Therefore, it is essential to remove the reflection interference in infrared images. With the continuous application and expansion of neural networks in the field of image processing, researchers have tried to apply neural networks to remove image reflection. However, they have mainly focused on reflection interference removal in visible images and it is believed that no researchers have applied neural networks to remove reflection interference in infrared images. In this paper, the authors introduce the concept of a conditional generative adversarial network (cGAN) and propose an end-to-end trained network based on this with two types of loss: perceptual loss and adversarial loss. A self-built infrared reflection image dataset from an infrared camera is used. The experimental results demonstrate the effectiveness of this GAN for removing infrared image reflection.

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