A pulse array image sensor (PAIS) is a bionic image sensor that converts light intensity into a pulse sequence to reduce the data volume. The traditional tracking method is not suitable for the sparse data form because of the absence of grayscale information. A trajectory tracking method based on a Bayesian classifier is proposed to maximize the property of the pulse data. First, candidate points with the smallest interval distances are selected in the area of interest. Then the total pulse numbers in a specified period at different positions are gathered to compose the positive and negative feature vectors, which are used to train a naive Bayesian classifier. The classifier can exactly obtain positions from the candidate points, and features in the new tracking positions train and update the classifier. The two-step filtering target point tracking algorithm using the interval distance and Bayesian classifier requires only the raw pulse data without processing, which can maximize the advantages of the special data format and improve computing efficiency. In this way, the position information can be directly obtained from pulse data, and the problem of wasting computing resources on reconstructing grayscale images and treating them in the traditional way is avoided. Experiments were performed on both real filmed data and the public event camera datasets. Our method can obtain trajectories with a high accuracy and long tracking time. The tracking errors are in single digits. In the comparison experiments, although our method has a smaller data volume than other models that obtain both frame and event data, the results still show that it has a comparable performance to the state-of-the-art methods.
A digital domain dynamic path accumulation method for a time-delay-integration (TDI) image sensor that can realize on-chip compensation for image distortion caused by sensor vibration is proposed. Through the proposed method, the exposure signals are controlled to enter the corresponding accumulator according to the vibration vector, ensuring the synchronous accumulation of different stages of pixels on the same object. The behavior level model of the method is established. The structural similarity (SSIM) between images without distortion, distorted images, and images compensated for by the proposed method is simulated and analyzed to verify the effectiveness of the method. Compared with conventional TDI, the SSIM between images with and without vibration is improved from 0.2322 to 0.9858, as the vibration level is 1 pixel per stage. With fixed TDI stages and the vibration level varying from 0 to 2 pixels per stage, the SSIM of conventional TDI drops rapidly to about 0.2 while that of the dynamic path accumulation method maintains at about 0.95. The proposed method is suitable for an antivibration CMOS-TDI image sensor of remote imaging systems.
An analytical model of hybrid accumulation architecture based on charge-domain and digital-domain time-delay-integration complementary metal-oxide-semiconductor image sensor (TDI-CIS) in the scanning direction is proposed. Optical performance of signal-noise-ratio, dynamic range, and modulation transfer function of the charge-domain, digital-domain, and hybrid accumulation scheme is simulated and analyzed. The synthetical evaluation target (SET) is defined to obtain the best performance under different distribution methods of the charge-domain and digital-domain at a fixed TDI stage for a hybrid accumulation scheme. According to the simulation results, the hybrid accumulation scheme whose charge-domain accumulation stage is 8 and digital-domain accumulation stage is 16 has the optimal SET, which is 12.99% higher than a 128-stage digital-domain accumulation scheme and 25% higher than the 128-stage charge-domain accumulation scheme.
A mathematical model of time-gated FLIM SPAD image sensors was established in behavioral level by MATLAB. The process of time-gated detection was simulated which includes photons emission, avalanche triggering and the restoration of fluorescence lifetimes. A fluorescence lifetime map was used to model the virtual scene being photographed. In order to guide the design of FLIM SPAD image sensors, the impacts of some parameters of FLIM SPAD image sensors, such as DCR and timing jitter, were analyzed by the proposed model. The impacts of the above parameters on sensors quantified by the simulation results indicated that the FLIM SPAD image sensor can get a better performance with smaller DCR and shorter timing jitter.
In this paper, a mathematical model of TDI CMOS image sensors was established in behavioral level through MATLAB based on the principle of a TDI CMOS image sensor using temporal oversampling rolling shutter in the along-track direction. The geometric perspective and light energy transmission relationships between the scene and the image on the sensor are included in the proposed model. A graphical user interface (GUI) of the model was also established. A high resolution satellitic picture was used to model the virtual scene being photographed. The effectiveness of the proposed model was verified by computer simulations based on the satellitic picture. In order to guide the design of TDI CMOS image sensors, the impacts of some parameters of TDI CMOS image sensors including pixel pitch, pixel photosensitive size, and integration time on the performance of the sensors were researched through the proposed model. The impacts of the above parameters on the sensors were quantified by sensor’s modulation transfer function (MTF) of the along-track direction, which was calculated by slanted-edge method. The simulation results indicated that the TDI CMOS image sensor can get a better performance with smaller pixel photosensitive size and shorter integration time. The proposed model is useful in the process of researching and developing a TDI CMOS image sensor.
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