Sensitive test for sea mine identification based on polarization-aided image processing

Abstract

Techniques are widely sought to detect and identify sea mines. This issue is characterized by complicated mine shapes and underwater light propagation dependencies. In a preliminary study we use a preprocessing step for denoising underwater images before applying the algorithm for mine detection. Once a mine is detected, the protocol for identifying it is activated. Among many correlation filters, we have focused our attention on the asymmetric segmented phase-only filter for quantifying the recognition rate because it allows us to significantly increase the number of reference images in the fabrication of this filter. Yet they are not entirely satisfactory in terms of recognition rate and the obtained images revealed to be of low quality. In this report, we propose a way to improve upon this preliminary study by using a single wavelength polarimetric camera in order to denoise the images. This permits us to enhance images and improve depth visibility. We present illustrative results using in situ polarization imaging of a target through a milk-water mixture and demonstrate that our challenging objective of increasing the detection rate and decreasing the false alarm rate has been achieved.

A polarization-based smoke removal method for surgical images

“…ii) the cross-polarized channels eliminate dominance of radiance from superficial layers, which means the cross-polarized channel has a certain dehazing effect, and this is consistent with the conclusions in Ref. [23,25];…”

“…These methods are simple and direct but their dehazing effect is limited. Restoration approaches are usually based on various models that estimate the dehazed image color and intensity from the image based on specific priors or assumptions, for example, based on the dark channel prior [15], maximizing contrast [16], color lines prior [17], haze lines prior [18,19], color attenuation prior [20] and polarization based [21][22][23][24][25], etc. These methods usually have a better dehazed output, but the assumptions and prior information have limitations and are not applicable in all scenarios.…”

“…Even though there are examples of polarization imaging in outdoor scenes such as for foggy days [21], underwater imaging [22][23][24][25], and for biomedical image processing and tissue diagnosis [2][3][4][5], there are currently neither related research about polarization based surgical smoke removal, nor polarized surgical smoke datasets [1]. In this paper, we propose a polarization-based smoke removal method for biomedical images.…”

An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy

“…Polarization of light provides valuable information about scenes that cannot be obtained directly from intensity or spectral images and polarization images seek to obtain the vector nature of the optical field from the scene [1]. Polarization imaging is widely used in those fields, such as industrial inspection [2], environmental monitoring [3], biomedical diagnosis [4,5], marine detection [6][7][8], remote sensing [9][10][11], military reconnaissance [12][13][14], etc.…”

Resolution enhancement in active underwater polarization imaging with modulation transfer function analysis

“…Orthogonal imaging is introduced to suppress the single and part of the multiple-scattering photons to enhance the contrast between targets and background. Numerous approaches are available to enhance the contrast for target detection both in the laboratory [8,9] and in actual ocean environments. Dubreuil et al proved that orthogonal polarization imaging improves the performance of underwater target detection using correlation technology [10].…”