Research on polarization dehazing through the coaxial and multi-aperture polarimetric camera

Li, Xuan; Liu, Fei; Han, Peng; Yi, Wei; Zhao, Dahu; Shao, Xiaopeng; Zhao, Xiaoming

doi:10.1364/osac.2.002369

Cited by 7 publications

(8 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The imaging polarimeter is a device that can obtain four different linear polarization images simultaneously (linear-Stokes polarimeter) or three linear polarization images and one circular polarization image (full-Stokes polarimeter) with optimal designed structures. 91 The polarimeters are usually based on different technological aspects, such as division of time, [92][93][94][95] division of amplitude, 96 division of aperture, 60,97 division of focal plane, [98][99][100] and Fourier-based. [101][102][103][104] The imaging polarimeter has been thoroughly reviewed in Ref.…”

Section: Real-time Polarimetric Dehazing Methods Based On Imaging Polamentioning

confidence: 99%

Review of passive polarimetric dehazing methods

et al. 2021

View full text Add to dashboard Cite

The images acquired in haze conditions are significantly degraded due to the presence of atmospheric particles. These images have low contrast, poor visibility, and some information is lost as well. These characteristics severely hinder the further processing and the applications in which the images are being used. The polarimetric dehazing methods are effective for direct imaging and enhancing the imaging quality. In addition, polarimetric dehazing methods have the capability to cope with haze and other turbid mediums. Therefore, the polarimetric dehazing methods are extensively developed and used in different applications due to their superior performance. We present in detail the principles, the implementation techniques, and the advancements in the polarimetric dehazing methods. We believe that this work is the first in-depth review on the passive polarimetric dehazing methods.

show abstract

Section: Real-time Polarimetric Dehazing Methods Based On Imaging Polamentioning

confidence: 99%

Review of passive polarimetric dehazing methods

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Eqs. ( 4) and (5) show that there is only a phase difference between the two Fourier transforms, and the phase difference can be obtained by calculating their mutual power spectrum. Perform a Fourier inverse transform on both sides of Eq.…”

Section: Coarse Registration Of Polarized Imagesmentioning

confidence: 99%

“…However, there is no universal registration algorithm. Li Xuan et al [5] only considered the translation between four polarized images in the coaxial multi-aperture imaging system. In practical, the rotation and scaling between the four polarized images cannot be ignored.…”

Section: Introductionmentioning

confidence: 99%

Image registration method for full-Stokes-vector division-of-aperture polarimetric camera

Ren

Zhang

et al. 2023

International Conference on Optical and Photonic Engineering (icOPEN 2022)

View full text Add to dashboard Cite

Polarimetric imaging can significantly improve the quality of images captured under poor imaging conditions, these include enhancing visibility in fog, increasing image contrast under complicated background, highlighting details of targets by removing strong surface glare, etc. Compared with other polarimetric imaging systems, the full-Stokes-vector division-of-aperture polarimetric camera has obvious advantages such as the real-time imaging and the structural compactness, owing to its inherent capability of capturing the same scene's four images related to its full-Stokes vector simultaneously. However, the deviations among four polarized images are inevitable due to assembly errors of four subapertures and the corresponding imaging channels. In this paper, we propose a method to solve the image registration problem in such a kind camera. Firstly, the coarse image registration is implemented through the phase-only correlation algorithm; secondly, the feature points of the reference image and other three images under registration are extracted and matched by using the Speeded-up Robust Features (SURF) algorithm; finally, the affine transformation matrix between the reference image and each of the three images to be registered is obtained by using the RANSAC (i.e., Random Sample Consensus) optimization algorithm, respectively. The experimental results demonstrate that four polarized images are registered, which effectively enhance the image quality in terms of the degree-of-polarization (DoP), the angle-of-polarization (AoP), the structural similarity (SSIM) index, and the normalized mutual information (NMI) index.

show abstract

“…As a basic physical property of light different from intensity, polarization characteristic is closely related to the objectives' surface roughness, texture and material composition. Therefore, polarization imaging technology has a strong ability to detect targets in complex backgrounds and low visibility conditions [1][2][3]. Owing to these benefits, polarization imaging has been widely used in target detection [4,5], turbid media imaging [6,7], 3D reconstruction [8], biomedical image analysis [9][10][11] and material classification [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A new adaptive window‐based guided filtering and interpolation for polarization image demosaicing

Xie

Liu

Chen

2023

IET Image Processing

View full text Add to dashboard Cite

This paper presents a new adaptive window‐based guided filtering and interpolation for polarization image demosaicing. Considering the correlation between the polarization channels, the authors use the total intensity S0 as a guide image to guide the interpolation of all channels. The guided filtering is performed with a new adaptive window size selection technique. A novel iterative residual interpolation is proposed to construct accurate full resolution polarization. Experiments are conducted with the sample images from the demosaicking algorithms dataset. Objective evaluations demonstrate that the proposed algorithm can reduce root mean squared error by at least 27% over other methods. Subjective visual inspection can also verify the improvements in the clarity of objects in angle and degree of the linear polarization images.

show abstract

Research on polarization dehazing through the coaxial and multi-aperture polarimetric camera

Cited by 7 publications

References 22 publications

Review of passive polarimetric dehazing methods

Review of passive polarimetric dehazing methods

Image registration method for full-Stokes-vector division-of-aperture polarimetric camera

A new adaptive window‐based guided filtering and interpolation for polarization image demosaicing

Contact Info

Product

Resources

About