An Adaptive Enhancement Algorithm for Infrared Images

2015 ◽  
Author(s):  
Yan Zhou ◽  
Qingwu Li ◽  
Guanying Huo
Keyword(s):  
Infrared Images ◽  
Adaptive Enhancement ◽  
Enhancement Algorithm

An adaptive enhancement algorithm based on visual saliency for low illumination images

2021 ◽  
Author(s):  
Shenyi Qian ◽  
Yongsheng Shi ◽  
Huaiguang Wu ◽  
Jinhua Liu ◽  
Weiwei Zhang
Keyword(s):  
Visual Saliency ◽  
Adaptive Enhancement ◽  
Low Illumination ◽  
Enhancement Algorithm

FPGA Implementation of Real-Time Adaptive Bidirectional Equalization for Histogram

2012 ◽  
Vol 461 ◽  
pp. 215-219
Author(s):  
Yu Qian Zhao ◽  
Zhi Gang Li
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Processing Speed ◽  
Local Maximum ◽  
Histogram Equalization ◽  
Infrared Images ◽  
Single Frame ◽  
Processing Effects ◽  
Simulation Results ◽  
Enhancement Algorithm

According to the characteristics of infrared images, a contrast enhancement algorithm was presented. The principium of FPGA-based adaptive bidirectional plateau histogram equalization was given in this paper. The plateau value was obtained by finding local maximum and whole maximum in statistical histogram based on dimensional histogram statistic. Statistical histogram was modified by the plateau value and balanced in gray scale and gray spacing. Test data generated by single frame image, which was simulated by FPGA-based real-time adaptive bidirectional plateau histogram equalization. The simulation results indicates that the precept meet the requests well in both the image processing effects and processing speed

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.

scholarly journals Adaptive Enhancement Algorithm of High-Resolution Satellite Image Based on Feature Fusion

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Ruizhe Wang ◽  
Wang Xiao
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Feature Fusion ◽  
Satellite Image ◽  
Texture Features ◽  
Noise Removal ◽  
Enhancement Effect ◽  
Adaptive Enhancement ◽  
High Resolution Satellite Images ◽  
Enhancement Algorithm

Since the traditional adaptive enhancement algorithm of high-resolution satellite images has the problems of poor enhancement effect and long enhancement time, an adaptive enhancement algorithm of high-resolution satellite images based on feature fusion is proposed. The noise removal and quality enhancement areas of high-resolution satellite images are determined by collecting a priori information. On this basis, the histogram is used to equalize the high-resolution satellite images, and the local texture features of the images are extracted in combination with the local variance theory. According to the extracted features, the illumination components are estimated by Gaussian low-pass filtering. The illumination components are fused to complete the adaptive enhancement of high-resolution satellite images. Simulation results show that the proposed algorithm has a better adaptive enhancement effect, higher image definition, and shorter enhancement time.

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.

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.

Sign in / Sign up

Export Citation Format

Share Document