LAUSR

Abstract Resolution is one of the most important parameters of low-light-level (LLL) image intensifiers, reflecting the target detection performance of assembled night vision devices under  1 0 − 3 to  1 0 − 1 lx dark environment. The traditional methods of measuring this parameter are classified into subjective evaluation and objective test. The disadvantages of subjective evaluation are strong subjectivity and low accuracy, while the traditional objective test method shows the weaknesses of excessive human intervention and large time consumption. To address these problems, an objective evaluation method based on a model of image restoration and an applied model of image filtering is proposed, which makes use of the similarity between unit stripe pattern and standard stripe pattern to evaluate the recognizability of unit stripe pattern. Firstly, the region of interest (ROI) is cut out from the original image and preprocessed to acquire the clearer results. Then, a model of image restoration is utilized to recover the stripe information lost in image preprocessing. After that, individual unit images are segmented from ROI, laying the foundation for the calculation of unit stripe definition. To extract recognizable unit images from unit image set, an image filtering model composed of several discernible constraints are presented according to the similarity features between unit stripe pattern and standard stripe pattern. Finally, the definition of unit is represented by the weighted sum of the product of constraint score and proportion of the number of discernable images under the constraint to the total number of images in the unit. With the help of linear fitting algorithm, the resolution of LLL image intensifier is calculated by combining the unit resolution-definition correspondences with the limiting definition. To verify the effectiveness of this method, different types of image tubes are used for experiments, and the subjective evaluation method and the advanced objective evaluation technology are adopted as comparison. The experimental results demonstrate that the evaluation results of this method are in good agreement with the subjective judgment results, and the accuracy is higher, reflecting in the maximum deviation is 2.8 lp/mm. The time efficiency of this method is greatly improved compared with that of traditional objective evaluation method. Moreover, the repeatability experiment results reveal that the stability of this approach is superior to that of the cited techniques, and the maximum deviation of evaluation results is 1.2 lp/mm (the lowest). In general, this method can overcome the shortcomings of traditional subjective and objective evaluation methods, and provide an effective and feasible scheme for the standardized measurement of LLL image intensifier resolution.