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In underwater imaging scenarios, the scattering media could cause severe image degradation due to the backscatter veiling as well as signal attenuation. In this paper, we consider the polarization effect of the object, and propose a method of retrieving the objects radiance based on estimating the polarized-difference image of the target signal. We show with a real-world experiment that by taking into account the polarized-difference image of the target signal additionally, the quality of the underwater image can be effectively enhanced, which is particularly effective in the cases where both the object radiance and the backscatter contribute to the polarization, such as underwater detection of the artifact objects.

The underwater imaging could be severely degraded by the scattering media because of the backscattered light and signal attenuation, especially in the case of strong scattering for dense turbid medium. In this paper, we propose an improved method for recovering the underwater image combining the histogram stretching and polarimetric recovery in a proper way. In this method, we stretch the histograms of the orthogonal polarization images while maintaining the polarization relation between them, and then, based on the processed orthogonal polarization images, the recovered image with higher quality can be obtained by the traditional polarimetric recovery method. Several groups of experimental results demonstrate that the quality of underwater images can be effectively enhanced by our method, and its performance is better than that of the traditional polarimetric recovery method. In particular, the proposed method is also quite effective in the condition of dense turbid medium.

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Based on the research of the traditional empirical mode decomposition (EMD) method, we proposed a modified EMD algorithm for the detected signal processing in tunable diode laser absorption spectroscopy. The modified EMD algorithm introduced Savitzky-Golay filtering and cross-correlation operation into the traditional EMD algorithm and reconstructed the signal by using the cross-correlation coefficients effectively. Based on the modified EMD algorithm in theory, the second harmonic component analysis was simulated by comparing with some other filtering algorithms. The experiments system was performed for carbon monoxide (CO) concentration detection. Comparing the sensing performances without and with using EMD-FCR and other filtered methods, the experimental results show that the signal-to-noise ratio of the system was significantly improved from 7.32 to 14.31 dB by EMD-FCR corresponding to one absorption line of CO at 1567.32 nm, leading to the minimum detection limit of 2 ppm. The accuracy and stability of the system are both improved by proposing the modified EMD algorithm.

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