A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS
The digital time delay integration (digital TDI) technology of the complementary metal-oxide-semiconductor (CMOS) image sensor has been widely adopted and developed in the optical remote sensing field. However, the details of targets that have low illumination or low contrast in scenarios of high co...
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doaj-57e73a929dec43b19339837742d9715b2020-11-25T01:03:31ZengMDPI AGApplied Sciences2076-34172017-10-01710108910.3390/app7101089app7101089A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOSTaiji Lan0Xucheng Xue1Junlin Li2Chengshan Han3Kehui Long4Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaThe digital time delay integration (digital TDI) technology of the complementary metal-oxide-semiconductor (CMOS) image sensor has been widely adopted and developed in the optical remote sensing field. However, the details of targets that have low illumination or low contrast in scenarios of high contrast are often drowned out because of the superposition of multi-stage images in digital domain multiplies the read noise and the dark noise, thus limiting the imaging dynamic range. Through an in-depth analysis of the information transfer model of digital TDI, this paper attempts to explore effective ways to overcome this issue. Based on the evaluation and analysis of multi-stage images, the entropy-maximized adaptive histogram equalization (EMAHE) algorithm is proposed to improve the ability of images to express the details of dark or low-contrast targets. Furthermore, in this paper, an image fusion method is utilized based on gradient pyramid decomposition and entropy weighting of different TDI stage images, which can improve the detection ability of the digital TDI CMOS for complex scenes with high contrast, and obtain images that are suitable for recognition by the human eye. The experimental results show that the proposed methods can effectively improve the high-dynamic-range imaging (HDRI) capability of the digital TDI CMOS. The obtained images have greater entropy and average gradients.https://www.mdpi.com/2076-3417/7/10/1089optical remote sensingdigital TDI CMOShigh-dynamic-range imagingEMAHEgradient pyramid decompositionimage fusion |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Taiji Lan Xucheng Xue Junlin Li Chengshan Han Kehui Long |
spellingShingle |
Taiji Lan Xucheng Xue Junlin Li Chengshan Han Kehui Long A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS Applied Sciences optical remote sensing digital TDI CMOS high-dynamic-range imaging EMAHE gradient pyramid decomposition image fusion |
author_facet |
Taiji Lan Xucheng Xue Junlin Li Chengshan Han Kehui Long |
author_sort |
Taiji Lan |
title |
A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS |
title_short |
A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS |
title_full |
A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS |
title_fullStr |
A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS |
title_full_unstemmed |
A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS |
title_sort |
high-dynamic-range optical remote sensing imaging method for digital tdi cmos |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2017-10-01 |
description |
The digital time delay integration (digital TDI) technology of the complementary metal-oxide-semiconductor (CMOS) image sensor has been widely adopted and developed in the optical remote sensing field. However, the details of targets that have low illumination or low contrast in scenarios of high contrast are often drowned out because of the superposition of multi-stage images in digital domain multiplies the read noise and the dark noise, thus limiting the imaging dynamic range. Through an in-depth analysis of the information transfer model of digital TDI, this paper attempts to explore effective ways to overcome this issue. Based on the evaluation and analysis of multi-stage images, the entropy-maximized adaptive histogram equalization (EMAHE) algorithm is proposed to improve the ability of images to express the details of dark or low-contrast targets. Furthermore, in this paper, an image fusion method is utilized based on gradient pyramid decomposition and entropy weighting of different TDI stage images, which can improve the detection ability of the digital TDI CMOS for complex scenes with high contrast, and obtain images that are suitable for recognition by the human eye. The experimental results show that the proposed methods can effectively improve the high-dynamic-range imaging (HDRI) capability of the digital TDI CMOS. The obtained images have greater entropy and average gradients. |
topic |
optical remote sensing digital TDI CMOS high-dynamic-range imaging EMAHE gradient pyramid decomposition image fusion |
url |
https://www.mdpi.com/2076-3417/7/10/1089 |
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