Objective

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Infrared digital TDI(time delay integration) first converts analog signals into digital ones and accumulates time delay integration signals unlike traditional infrared analog TDI. Its exposure method is highly flexible and could improve system detection sensitivity and the signal-to-noise ratio of the target. Thus

infrared digital TDI is widely used in aerospace remote sensing applications. An infrared digital TDI image system usually works through scanning

along with the characteristic of gaze because the system could be regarded as a small area array detector. For information processing

infrared digital TDI imaging non-uniformity is the key factor in limiting image quality. Reducing the non-uniformity of the output image is of great significance to the research and application of target detector and identification.

Method

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This study establishes an imaging input and output model by analyzing every part of the imaging system and discusses the influence of the parameters on the non-uniformity of imaging. This study also identifies the way to optimize the non-uniformity of the system. The non-uniformity correction of images includes blind element compensation and non-uniformity correction of an effective pixel. The compensating rate of the blind pixel is improved by iterating the compensated blind pixel with field pixel substitution and field pixel average. The response characteristics of all pixels are analyzed

and the nonlinearity between the grayscale output and the input energy is corrected by the optimized target calibration curve. The non-uniformity in the non-scanning direction is further corrected by introducing the correction factor.

Result

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Blackbody calibration was performed by using a domestic 640×8 medium-wave infrared TDI detector. The two-point method

multi-point method

and our method were used for image non-uniformity correction. The blackbody temperature of radiation calibration ranged from 30℃ to 56℃

and the pixel response tended to saturate higher than 56℃. The integration time of the detector is fixed at the typical time for imaging of 0.4 ms. The two-point method takes 30℃ and 56℃ pixel response data as original data to estimate the pixel response value between them and the multi-point method takes the data from 30℃ to 56℃ every 2℃ interval. An observation of the response curve of the sampled pixels shows good linearity of the pixel response curve from 30℃ to 50℃; the curve from 50℃ to 56℃ indicates nonlinearity. Correction result shows that non-uniformity of 7.45% and 7.31% at 35℃ and 45℃ is better than that of 8.26% at 53℃ with the two-point method because the two-point data that estimate pixel value needs the pixel signal to fit a straight line between points. Unlike the two-point method

the multi-point method could take the two nearest points to compute the pixel value and consider the linearity between the two nearest points only. The non-uniformity result at a different temperature is approximately 5% better than the result of the two-point method. On the basis of the multi-point data correction

the distributions of all the pixel response curves are considered

and a reasonable target curve is chosen as the correction curve. Therefore

nonlinear fitting is added between the multi-point data

and the non-uniformity value is reduced to approximately 4% at each temperature

which indicates that the method is effective. An imaging experiment was conducted in the real-world environment

and a few pictures were processed according to the radiation calibration data. The horizontal stripes on the obtained infrared TDI images are reduced and weakened after correction with the proposed methods.

Conclusion

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An analysis of the whole link for the target scene from the optical signal to the electrical signal clearly identifies the specific parameters that affect image non-uniformity. This finding has reference significance for the design of infrared digital TDI imaging systems. Blind pixel compensation and non-uniformity correction of the infrared digital TDI imaging system were performed by using the proposed method. The non-uniformity of the image was greatly decreased

and the effectiveness of the method was verified.