Aiming at the drawback of single sensor detection, the multi-sensor fusion technology is used to study the near ground infrared weak and small target detection based on fuzzy integrated decision-level image fusion. Firstly, the ILCM (improved local contrast mechanism) operator is used to calculate the infrared image saliency by using the image subblock instead of the pixel in contrast calculation. Then, the significance threshold ROI (region of interest) is introduced to eliminate the influence of the background, and the fusion region is divided by the region correlation mapping. Finally, the target fuzzy membership degree is calculated for the single sensor image according to the proposed RM (region matching) and FM (fuzzy membership) fuzzy features, and the infrared target is obtained by the fuzzy synthesis method. Experiments show that the proposed algorithm has good robustness and strong anti-interference ability for the infrared weak and small target detection in complex near ground background, and it has better target detection effect than single sensor.
Aiming at the problems existing in the effect evaluation of pattern painting camouflage, such as evaluating indicate simplification and nonobjectivity, this paper proposes a new method for effect evaluation of pattern painting camouflage based on entropy weighted similarity. According to the object and purpose of pattern painting camouflage assessment, five characteristic evaluating indicators of target image and its background, namely, hue, brightness, shape, texture and speckle, are selected synthetically, and the weight of each evaluating indicator affecting the whole evaluation result is determined by using entropy weight method. The different patterns of painting camouflage with some specific backgrounds are selected for comprehensive evaluation, meanwhile, these camouflage painting patterns are evaluated by the classic grey clustering decision algorithm, and finally the evaluating results of two methods are compared. The results show that the conclusions obtained by the two different evaluation methods are consistent and support mutual verification, which indicates that the proposed method in this paper is feasible and effective for the effect evaluation of pattern painting camouflage.
In contrast to detection in the sky or sea background, infrared small target detection in the near-earth background shows its own particularity and complexity. In this paper, an infrared image preprocessing algorithm using dark image processing and improved K-SVD algorithm is proposed. In the first place, an infrared image model in the near-earth background is constructed. Due to the similar characteristic of low contrast between infrared images and foggy images, we propose an analogical method that analogizes infrared images as foggy images. On this basic, theories of image dehazing can be employed in the process. In this preprocessing algorithm, near-earth background suppression in infrared images is achieved by dark image processing method. After background suppression, an improved K-SVD algorithm based on NLM algorithm is applied for image denoising. Considering relevant information of different image blocks and the orthogonality between residual terms after denoising and chosen atoms, a regularized constraint represent for image self-similarity information is introduced to improve K-SVD algorithm. Experiments show that the proposed preprocessing algorithm can effectively suppress near-earth background, enhance the contrast between target and its peripheral region, and improve the performance of infrared image preprocessing.
The general scalar diffractive theory for Gaussian beam has been investigated. The two-zone and three-zone annular phase-only pupil filters are adopted to provide specific numerical descriptions of improvement of DOF, respectively. The simulated results show that the annular phase-only pupil filters can be used to control the DOF of the optical system. For the well designed filters they can help improve the DOF in the axial direction and increase the resolution in the transverse direction, simultaneously. However, the Strehl ratio of the optical system maybe decline and the side-lobe to peak intensity ratio will increase with the improvement of the DOF which is hard for the optical imaging. Comparison results show that the two kinds of three-zone annular phase-only pupils have the same impact on the control of the light intensity distribution.
The general super-resolving theories for Gaussian beam have been investigated. The three-zone amplitude pupils and phase-only pupils are adopted to provide specific numerical descriptions of improvement of DOF, respectively. Simulated results of comparison between Gaussian beam and Uniform amplitude beam have been presented. Furthermore, some useful advices for the design of super-resolving pupils to increase DOF of the optical system based on Gaussian beam are given.