The spectral resolution of The Temporally and Spatially Modulated Fourier Transform Imaging Spectrometer (TSMFTIS) is mainly determined by the optical focal length, lateral shear, and the performance of the infrared focal plane array (FPA) in combination. However, due to the limited number and density of pixels in the FPA, the lateral shear of the optical system is constrained, resulting in the overall spectral resolution of the instrument unable to be higher. Therefore, this paper proposes achieving super-sampling of the detector for interference images by performing multiple subpixel shifts on the FPA detector. This method supports the continuous increase of lateral shear amount, ultimately improving the overall spectral resolution of the instrument. Experimental results show that using a 384x288 uncooled infrared FPA and under conditions of eightfold super-sampling and 8000μm lateral shear, the instrument's spectral resolution increased from 15.75 cm-1 to 2.31 cm-1.
The temporally and spatially modulated Fourier transform imaging spectrometer (TSMFTIS) has the merits of high optical throughput, good mechanical stability, and simple interference configuration. However, the number and the density of pixels in the infrared (IR) focal plane array limit the spectral resolution of TSMFTIS. Thus, we proposed the interferometric supersampling levering multiple sub-pixel translations of the focal plane array detector to realize the supersampling of the interference fringes and improve the system’s spectral resolution. The experimental results show that 2.31 cm−1 spectral resolution is achieved by employing a 384×288 uncooled IR detector array.
High-resolution spectral imaging of objects on ocean surfaces is difficult, because the position of these objects and the water waves on the ocean surface, as well as the illumination, vary over time. We propose a method for the reconstruction of spectral images of ocean surfaces based on the response of a standard RGB (sRGB) imaging system and a group of ocean spectrum samples. First, we measured the spectral reflectance of a typical ocean surface in the visible band using a standard spectroradiometer. Using transformations in the hue, saturation, and brightness dimensions, we then expanded these measurements to form a reference group of spectral reflectance samples along with their corresponding sRGB values. Following this, we established a method for reconstructing the spectral image cube of an ocean surface from a single sRGB image using a spectrum dictionary and RGB value matching. Our technique thus eliminates the problem of conversion from a three-dimensional RGB space to a multidimensional spectral space faced by conventional spectral reconstruction methods. In our experiments, we captured a series of sRGB standard images of a typical ocean surface using a standard digital color camera, and then reconstructed the spectral image cube from 400 to 700 nm using a 5-nm interval. Based on assessment of the quality of the reconstructed spectral images, our technique demonstrates desirable performance with respect to spectral distribution and spatial resolution.
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