Resolution enhancement algorithm based on infrared digital holography imaging through flame
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摘要:
近年来,高温干扰遮蔽情况下利用红外热成像与数字全息成像相结合的新技术观察火场中目标成为时下的研究重点。理论上火焰和浓烟对长波长的红外数字全息成像没有影响,但在现实火场环境中,燃烧物的大颗粒灰尘将会干扰光路,严重增加了全息图重建图像的噪声。本文提出了一种新的图像处理算法来抑制红外数字全息重建的噪声。该算法利用双边滤波器配合拉普拉斯金字塔算法将全息重建图像的细节和能量层分开,再对细节层进行滤波,然后用反向拉普拉斯金字塔算法将分离的层叠加回重建图像中,从而提高重建像的分辨率,并通过模拟火场环境验证了该算法对改善红外数字全息图重建像的分辨率具有显著效果。
Abstract:In recent years, the use of new technologies combining infrared thermal imaging and digital holographic imaging to observe the targets in the fire field has become a current research focus. In theory, flame and smoke have no effect on long-wavelength infrared digital holography, but in the real fire environment, large particles of dust from the combustion will interfere with the light path, seriously increasing the reconstruction noise of the hologram. This paper proposes a new image processing algorithm to suppress the noise of infrared digital holographic reconstruction. The algorithm uses a bilateral filter combined with the Laplacian pyramid algorithm to separate the details and energy layers of the holographic reconstructed image, filters the detail layer, and then superimposes the separated layers back into the reconstructed image by the inverse Laplacian pyramid algorithm. Therefore, the resolution of the reconstructed image is improved, and the simulation of the fire field environment proves that the algorithm has a significant effect on improving the resolution of the reconstructed image of the infrared digital hologram.
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Overview: In general, the target observation methods are mostly concentrated in the visible and infrared light bands, and the target and scene are observed by the imaging devices of the corresponding bands respectively. However, in areas where fires occur, the mere use of traditional imaging observations does not meet the requirements. On the one hand, due to the shielding effect of fire and smoke, the short-wavelength scattering effect in the visible light band is obvious, and it is not suitable for such turbid medium. Therefore, it is almost impossible to see the target situation in the fire field by means of visible light observation, which brings extremes to search and rescue. On the other hand, the use of infrared thermal imaging alone has certain disadvantages. Although long-wave infrared light can transmit dust and haze to a certain extent, its fundamental infrared thermal imaging is a kind of temperature difference imaging. If the target temperature is too high in the observed scene, it will cause the pixel response on the focal plane. The saturation makes it impossible to observe the target normally. In recent years, the use of new technologies combining infrared thermal imaging and digital holographic imaging to observe the target in the fire field has become the focus of research. In theory, flame and smoke have no effect on long-wavelength infrared digital holography, but in the real fire environment, large particles of dust from the combustion will interfere with the light path, which seriously increases the noise of the hologram reconstructed image. Our optical device is based on simple Mach-Zender interference. No special equipment is needed in the optical device. After collecting the interference fringe image of the imaging target and reconstructing the image, a new image processing algorithm is proposed to suppress the noise of infrared digital holographic reconstruction. The algorithm uses a bilateral filter combined with the Laplacian pyramid algorithm to separate the details and energy layers of the holographic reconstructed image, filters the detail layer, and then superimposes the separated layers back into the reconstructed image by the inverse Laplacian pyramid algorithm. In order to improve the resolution of the reconstructed image, and by simulating the fire field environment, the algorithm can effectively enhance the image resolution of the transparent digital smoke holographic image. The algorithm has the advantages of simple calculation and easy implementation, which can greatly reduce speckle noise and improve the details of reconstructed images. Experimental results show that this new algorithm has good performance.
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图 11 多种算法处理下的透火焰成像图。(a)多图片取均值算法[4];(b)自适应直方图算法[18];(c)基于特征分析的红外图像边缘增强算法[19];(d)本文提出的算法
Figure 11. Through flame imaging image processed by various algorithms. (a) Multiple images are cumulatively averaged[4]; (b) Adaptive histogram equalization algorithm[18]; (c) Edge enhancement and noise suppression for infrared image based on feature analysis[19]; (d) Algorithm proposed in this paper
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