Resolution enhancement algorithm based on infrared digital holography imaging through flame

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.