Ji Chen

Bio: Ji Chen is an academic researcher. The author has contributed to research in topics: Compressed sensing & Channel (broadcasting). The author has an hindex of 2, co-authored 3 publications receiving 15 citations.

Band optimization of passive methane gas leak detection based on uncooled infrared focal plane array.

Abstract: Current methane gas leak detection technology uses infrared imaging in the medium wave (MW) or long wave (LW) bands, essentially applying cooled infrared detectors. In this study, a simplified three-layer radiative transfer model is adopted based on methane gas detection theory, considering background radiation, atmospheric infrared absorption, gas absorption, and emission characteristics to analyze the contrast of methane gas thermography in different infrared bands. The analysis results suggest that under certain conditions, the 6.6–8.6 μm LW band provides higher contrast compared to the 3–5 μm MW band. The optimal imaging wavelength band is selected according to imaging contrast advantages and disadvantages, and infrared optical systems and infrared filters are designed and optimized. We build a passive methane gas leak detection system based on uncooled infrared focal plane array detectors. By collecting gas images under different conditions, the imaging detection capabilities for methane gas leaks in the MW and LW bands in a laboratory environment are compared. Finally, the developing trends in methane gas detection technology are analyzed.

Forest fire prevention monitoring system based on double-wave-band fusion theory

Abstract: The invention provides a forest fire prevention monitoring system based on a double-wave-band fusion theory. The monitoring system comprises a monitoring center and a plurality of monitoring points. Each monitoring point comprises a visible light camera a1, an infrared camera a2, a natural color image fusion module b and a video coding module c. A base station comprises a wireless transmission module d, a central processor e and a screen display wall f. The system makes full use of respective advantages of the visible light camera and the infrared camera, combines the double-wave-band fusion theory and achieves all-day, real time and high-efficiency monitoring of a forest cover area.

Band optimization of passive methane gas leak detection based on uncooled infrared focal plane array: publisher's note.

Abstract: This publisher’s note amends the author listing in Appl. Opt.57, 3991 (2018)APOPAI0003-693510.1364/AO.57.003991.

Hankel Structured Low Rank and Sparse Representation Via L0-Norm Optimization for Compressed Ultrasound Plane Wave Signal Reconstruction

Abstract: Ultrasound plane wave imaging is widely used in many applications thanks to its capability in reaching high frame rates. However, the amount of data acquisition and storage in a period of time can become a bottleneck in ultrasound system design for thousands frames per second. In our previous study, we proposed a low-rank and joint-sparse model to reduce the amount of sampled channel data of focused beam imaging by considering all the received data as a 2D matrix. However, for a single plane wave transmission, the number of channels is limited and the low-rank property of the received data matrix is no longer achieved. In this study, a L 0 -norm based Hankel structured low-rank and sparse model is proposed to reduce the channel data. An optimization algorithm, based on the alternating direction method of multipliers (ADMM), is proposed to efficiently solve the resulting optimization problem. The performance of the proposed approach was evaluated using the data published in Plane Wave Imaging Challenge in Medical Ultrasound (PICMUS) in 2016. Results on channel and plane wave data show that the proposed method is better adapted to the ultrasound channel signal and can recover the image with fewer samples than the conventional CS method.

Optical Gas Imaging With Uncooled Thermal Imaging Camera - Impact of Warm Filters and Elevated Background Temperature

Abstract: The goal of the presented article is to investigate the impact of warm filters and elevated background temperature on the operation of an uncooled wideband camera used for optical gas imaging (OGI). The noise equivalent temperature difference (NETD) parameter is measured for a VOx wideband OGI camera built for the purpose of the experiments, with and without an interference filter. The results demonstrate that warm filters have a clear effect on the performance of the OGI camera. Based on the standard NETD measurement procedures, a camera-scene noise equivalent temperature difference (CSNETD) parameter is proposed to quantify both the camera and scene noise. The CSNETD measurements are used to evaluate the impact of elevated background temperature on the performance of the OGI camera. Finally, the camera is used to image methane leaks in the mid-wave infrared (MWIR) and long-wave infrared (LWIR) bands. The results are consistent with the presented NETD/CSNETD measurements and confirm the impact of warm filters and elevated background temperature on the operation of the uncooled thermal imaging camera.

Simultaneous determination of gas leakage location and leakage rate based on local temperature gradient

Abstract: In this study, a quantitative non-contact detection method for gas leakage problem based on infrared thermography technology is developed. First, the relationship between the gas leakage rate and the temperature gradient at the edge of the leaking hole is established based on thermodynamics, dimensional analysis and numerical methods. Second, the temperature fields surrounding the gas leakage location are extracted using an infrared thermal imager. Both the gas leakage location and leakage rate are obtained for the damaged rubber seals. Finally, the detections of gas leakage location with arbitrary shape and no obvious temperature difference are discussed and generalized. These results will play an important role in detecting the leakage rate for the damaged seal structures or containers.

Adaptive clip-limit-based bi-histogram equalization algorithm for infrared image enhancement.

Abstract: Infrared (IR) images are basically low-contrast in nature; hence, it is essential to enhance the contrast of IR images to facilitate real-life applications. This work proposes a novel adaptive clip-limit-oriented bi-histogram equalization (bi-HE) method for enhancing IR images. HE methods are simple in implementation but often cause over-enhancement due to the presence of long spikes. To reduce long spikes, this work suggests to apply a log-power operation on the histogram, where the log operation reduces the long spikes, and power transformation regains the shape of the histogram. First, a histogram separation point is generated applying the mean of the multi-peaks of the input histogram. After that, an alteration in the input histogram is done using the log-power process. Subsequently, a clipping operation on the altered histogram followed by redistribution of the clipped portion is performed to restrict over-enhancement. Next, the modified histogram is sub-divided using the histogram separation point. Finally, the modified sub-histograms are equalized independently. Simulation results show that the suggested method effectively improves the contrast of IR images. Visual quality evaluations and quantitative assessment demonstrate that the suggested method outperforms the state-of-the-art algorithms.