Two-point Correction Algorithm Research Articles

Lightweight and Real-Time Infrared Image Processor Based on FPGA.

This paper presents an FPGA-based lightweight and real-time infrared image processor based on a series of hardware-oriented lightweight algorithms. The two-point correction algorithm based on blackbody radiation is introduced to calibrate the non-uniformity of the sensor. With precomputed gain and offset matrices, the design can achieve real-time non-uniformity correction with a resolution of 640×480. The blind pixel detection algorithm employs the first-level approximation to simplify multiple iterative computations. The blind pixel compensation algorithm in our design is constructed on the side-window-filtering method. The results of eight convolution kernels for side windows are computed simultaneously to improve the processing speed. Due to the proposed side-window-filtering-based blind pixel compensation algorithm, blind pixels can be effectively compensated while details in the image are preserved. Before image output, we also incorporated lightweight histogram equalization to make the processed image more easily observable to the human eyes. The proposed lightweight infrared image processor is implemented on Xilinx XC7A100T-2. Our proposed lightweight infrared image processor costs 10,894 LUTs, 9367 FFs, 4 BRAMs, and 5 DSP48. Under a 50 MHz clock, the processor achieves a speed of 30 frames per second at the cost of 1800 mW. The maximum operating frequency of our proposed processor can reach 186 MHz. Compared with existing similar works, our proposed infrared image processor incurs minimal resource overhead and has lower power consumption.

Adaptive section non-uniformity correction method of short-wave infrared star images for a star tracker.

Using a short-wave infrared (SWIR) camera to improve daytime star detection ability has become a trend for near-ground star trackers. However, the noise of SWIR star images greatly decreases the accuracy of the attitude measurement results. Aiming at a real-time application of the star tracker, an adaptive section non-uniformity correction method based on the two-point correction algorithm for SWIR star images is proposed. The correction parameters of different sections are first calculated after the defective pixels are detected and excluded, and the real-time image is corrected using adaptive section parameters according to its gray value distribution. Finally, the defective pixels are compensated for by their adjacent corrected pixels. The correction results of both simulated and live-shot star images have verified the validity of the proposed method. It adapts to different sky background radiation, which is effective for the application of a star tracker. By comparing with other linear correction methods, it has the advantages of low calculation complexity, better real-time performance, and easier implementation in the hardware.

Coal Mine Personnel Safety Monitoring Technology Based on Uncooled Infrared Focal Plane Technology

In an effort to overcome the difficulty of real-time early warning via traditional infrared imaging technology caused by the complex working environment in coal mines, this paper proposes a mine early warning method based on uncooled infrared focal plane technology. The infrared thermal spectrogram of the detected object was visually displayed in a pseudo-color image with high resolution and high sensitivity, which can realize the real-time detection and early warning of personnel safety in modern mines. The multipoint compression correction algorithm based on human visual characteristics divided the response units of all acquisition units into gray intervals according to a threshold value, then the corresponding parameters were set in different intervals, and finally, each interval was compressed using a two-point correction algorithm. The volume of stored data was the sum of the calibration curve and the data from an encode table corrected by a MATLAB simulation, and the number of CPU cycles was run by a CCS 3.3 clock calculation algorithm. The results showed that when the temperature of the blackbody reached 115 °C, the nonuniformity before correction was 6.32%, and the nonuniformity after the multipoint correction of human eyes was 2.99%, which implied that the algorithm proposed in this paper had good denoising ability. The number of CPU cycles occupied by this algorithm was 18,257,363 cycles/frame with a frequency of 29.97 Hz. The sharpness of the compressed infrared images was obviously improved, and the uniformity was better. The method proposed in this paper can meet the need for modern mine personnel search and rescue, equipment supervision and dangerous area detection and other early warning requirements so as to achieve the goal of developing smart mines and ensuring safety in coal mine production.

Two-Point Multi-Section Linear Nonuniformity Correction of IRFPA Based on FPGA

The two-point multi-section method has higher precision than two-point correction algorithm and had lower operation load than multi-point correction algorithm. We realized the two-point multi-section method by the use of FPGA hardware module.

Novel real-time nonuniformity correction solution for infrared focal plane arrays based on S-curve model

Detectors of infrared focal plane arrays are, in the nature of their photoresponse, nonuniform. Response curves are nonlinear. In view of this, a novel nonuniformity correction algorithm based on the S-curve nonlinear response model and its simplified correction algorithm is proposed. The algorithm is an essential calibration and interpolation correction based on an analytical formula. It requires calibrating in advance, but possesses higher correction precision and wider applicative response range, which is particularly applicable to uncooled infrared focal plane arrays. Borrowing ideas from look-up tables, a real-time hardware correction system, which provides an experimental platform for contrasting different algorithms, is expounded. Experimental results validate that the proposed S-curve model-based algorithm does much better than the two-point correction algorithm and the simplified S-curve model-based correction algorithm.

在轨完成CCD非均匀性校正的方法

In order to get space camera image with good uniformity,a method of real-time TDI-CCD non-uniformity correction in orbit using XQ2VP40 FPGA is studied.Firstly the principle of CCD non-uniformity correction is analyzed,a two-point correction algorithm of half saturation gray and dark field gray is proposed,then the architecture of space cameras is introduced and correction algorithm utilizing FPGA is realized,finally the effect is proved by experimental result.The experimental results show that the method of CCD non-uniformity correcting is feasible,for the TDI-CCD whose non-uniformity is 5%,the non-uniformity is less than 1% after correction.

Test and evaluation of reference-based nonuniformity correction methods for microbolometer infrared detectors

AbstractIn the paper, reference-based nonuniformity correction methods for microbolometer infrared detectors are discussed and tested. In order to evaluate their effectiveness, a complete readout circuit for amorphous silicon microbolometer focal plane array has been designed. The tests were carried out on a developed stand including several extended blackbodies. Some modification of standard two-point correction algorithm incorporating detectors response at external shutter to compensate offset drift is also proposed. The obtained results are presented.

Solution for the nonuniformity correction of infrared focal plane arrays

Based on the S-curve model of the detector response of infrared focal plan arrays (IRFPAs), an improved two-point correction algorithm is presented. The algorithm first transforms the nonlinear image data into linear data and then uses the normal two-point algorithm to correct the linear data. The algorithm can effectively overcome the influence of nonlinearity of the detector's response, and it enlarges the correction precision and the dynamic range of the response. A real-time imaging-signal-processing system for IRFPAs that is based on a digital signal processor and field-programmable gate arrays is also presented. The nonuniformity correction capability of the presented solution is validated by experimental imaging procedures of a 128 x 128 pixel IRFPA camera prototype.

New improved nonuniformity correction for infrared focal plane arrays

The nonuniformity correction for infrared focal plane arrays (IRFPA) is generally implemented in engineering by using the two-point correction algorithm. However, its correction precision is reduced by the response non-linearity of IRFPA detectors. In this paper, using the “S”-curve model to approximate the response of IRFPA detectors, an improved two-point correction algorithm is presented. The algorithm firstly transforms the non-linear image data to linear ones, and then uses the normal two-point algorithm to correct the linear data. It can effectively overcome the influence of the response non-linearity of the detectors. The experiments demonstrate the high correction precision of the new correction algorithm.