In this paper, we analyze and experimentally demonstrate the medium-wave infrared (MWIR) imaging ability based on optical readout bimaterial microcantilever focal plane array (FPA) uncooled infrared imaging system. Multiband infrared imaging technology has been a hotspot in the field of infrared imaging. In the infrared band, medium-wave infrared (3~5 μm) has minimal attenuation of atmospheric infrared window, and it also covers many atomic and molecular absorption peak. Imaging study on MWIR radiation source also appears particularly important. First of all, we introduce the bimaterial microcantilever IR sensing principle and the fabrication of the bimaterial microcantilever FPA. Secondly, the paper introduces the theory of the optical-thermal-mechnical reading based on FPA. Finally, the experimental platform was constructed to conduct the MWIR imaging experiment. The medium-wave infrared radiation source consists of a continuous-wave optical parametric oscillator (OPO) that is pumped by a polarization-maintained, single-mode fiber amplifier. The length of the 50mm periodically polarized LiNbO3 crystal (5%MgO) is used as the nonlinear crystal. The stable cavity of the ring is designed, and the output of the 3~4 μm band is realized by the design of the nonlinear crystal polarization period. And the FPA employed in our experiment contains 256×256 pixels fabricated on a glass substrate, whose working bandwidth is covering the three IR atmospheric windows. The experimental results show that the bimaterial microcantilever FPA has a good imaging ability to the MWIR sources.
This paper proposes and experimentally demonstrates a new denoising and hole-filling algorithm through discrete points removal and bilinear interpolation based on the bi-material cantilever FPA infrared imaging system. In practice, because of the limitation of FPA manufacturing process and optical readout system, the quality of obtained images is always not satisfying. A lot of noise and holes appear in the images, which restrict the application of the infrared imaging system. After analyzing the causes of noise and holes, an algorithm is presented to improve the quality of infrared images. Firstly, the statistic characteristics such as probability histograms of images with noise are analyzed in great detail. Then, IR images are denoised by the method of discrete points removal. Second, the holes are filled by bilinear interpolation. In this step, the reference points are found through partial derivative method instead of using the edge points of the holes simply. It can detect the real points effectively and enable the holes much closer to the true values. Finally, the algorithm is applied to different infrared images successfully. Experimental results show that the IR images can be denoised effectively and the SNRs are improved substantially. Meanwhile, the filling ratios of target holes reach as high as 95% and the visual quality is achieved well. It proves that the algorithm has the advantages of high speed, great precision and easy implement. It is a highly efficient real-time image processing algorithm for bi-material micro-cantilever FPA infrared imaging system.
This paper proposes a method to recover the pulse signal with the theory of lock-in amplifier and calculates the oxygen saturation. The pulse signal is obtained based on the method of Photoplethysmography (PPG). We use a LED as the light source and a photoelectric diode as the receiver to get a measured pulse wave. Because the pulse wave obtained by this method is easily disturbed by motion artifact, we use an electrocardiogram (ECG) signal to aid PPG measurement. Firstly, the ECG signal is processed by the Fast Fourier Transform (FFT) and get the heart rate. Secondly, with the value of heart rate, a typical noise free pulse waveform can be constructed. Finally, we use it as a reference input to get a recovered pulse wave by the theory of lock-in amplifier. Thus, the value of oxygen saturation can be calculated accurately through two recovered pulse waveforms of red (660nm) and infrared (940nm) light. Some volunteers were tested. The correlation coefficient between the experimental data and the data provided by a reference instrument is 0.98, proving that this method has high reliability and utility in motion.
Low order aberration was founded when focused Gaussian beam imaging at Kodak KAI -16000 image detector, which is integrated with lenslet array. Effect of focused Gaussian beam and numerical simulation calculation of the aberration were presented in this paper. First, we set up a model of optical imaging system based on previous experiment. Focused Gaussian beam passed through a pinhole and was received by Kodak KAI -16000 image detector whose microlenses of lenslet array were exactly focused on sensor surface. Then, we illustrated the characteristics of focused Gaussian beam and the effect of relative space position relations between waist of Gaussian beam and front spherical surface of microlenses to the aberration. Finally, we analyzed the main element of low order aberration and calculated the spherical aberration caused by lenslet array according to the results of above two steps. Our theoretical calculations shown that , the numerical simulation had a good agreement with the experimental result. Our research results proved that spherical aberration was the main element and made up about 93.44% of the 48 nm error, which was demonstrated in previous experiment. The spherical aberration is inversely proportional to the value of divergence distance between microlens and waist, and directly proportional to the value of the Gaussian beam waist radius.