Optical design of an imager with wide field-of-view (FOV) and high-resolution utilizes a monocentric objective lens in conjunction with an array of secondary optical lenses to achieve good performance. An intermediate image with uniform residual aberration throughout a wide FOV is obtained on a curved surface by the monocentric objective lens and then relayed to a sensor array by the secondary optical lenses. In this paper, we focus on the study of the monocentric objective lens and the surface type of its obtained curved image. Firstly, the equation of focal length is determined by ray tracing. The achromatic condition is obtained through first-order aberration theory. Accordingly, the initial configuration of the monocentric objective lens is determined, including the surface radii and reasonable glass combination. Secondly, a detailed calculation of the image positions is performed. The results show that the image surface is spherical when the object distance is much larger than the focal length. But it is aspheric when the object distance is comparable to the focal length. Finally, a mono-centric lens is optimumly designed, with a visible working wavelength band of 480-640nm, a focal length of 100mm, a wide FOV of 140°, and a large f-number of 5. Through imaging simulation and the image performance evaluation with ZEMAX, the theoretical calculations are verified.
The multi-focus image fusion technique is to extract the focus regions from source images and compose them together to form a clear image in the full field of view. In order to further improve the accuracy of focus region detection and ensure its efficiency, a novel multi-focus image fusion method in spatial domain, based on guided filter and mixed focus measure, is proposed in this paper. Firstly, a guided filter is employed as an edge-preserving smoothing operator to process the source images, and the difference operator is used between the filtered images and the source images to extract salient feature. Subsequently, the salient feature maps are measured by the mixed focus measure, combining the sum of energy of edge (SEOE) and the sum of local variance (SLV), to detect the focus regions, and the initial decision map is obtained. For holes of different sizes in the initial decision map, the closing operation and the small area removal strategy are used to fill and connect the truncated regions, and then the opening operation and the guide filter are used to optimize the decision map boundary to obtain the final decision map. Finally, the multi-focus fusion image is obtained by the pixel-wise weighted-averaging rule according to the final decision map. Simulation results demonstrate that the method is superior to some existing fusion methods on both subjective visual perception and objective evaluation metrics.
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