Compared with the normal low dynamic range (LDR) images, high dynamic range (HDR) images provide more dynamic range and image details. Although the existing techniques for generating HDR images have a good effect for static scenes, they usually produce artifacts on the HDR images for dynamic scenes. In recent years, some learningbased approaches are used to synthesize HDR images and get good results. However, there are also many problems, including the deficiency of explaining and the time-consuming training process. In this paper, we propose a novel approach to synthesize multi-view HDR images through fuzzy broad learning system (FBLS). We use a set of multi-view LDR images with different exposure as input and transfer corresponding Takagi-Sugeno (TS) fuzzy subsystems, then the structure is expanded in a wide sense in the "enhancement groups" which transfer from the TS fuzzy rules with nonlinear transformation. After integrating fuzzy subsystems and enhancement groups with the trained-well weight, the HDR image is generated. In FBLS, applying the incremental learning algorithm and the pseudoinverse method to compute the weights can greatly reduce the training time. In addition, the fuzzy system has better interpretability. In the learning process, IF-THEN fuzzy rules can effectively help the model to detect artifacts and reject them in the final HDR result. These advantages solve the problem of existing deep learning methods. Furthermore, we set up a new dataset of multi-view LDR images with corresponding HDR ground truth to train our system. Our experimental results show that our system can synthesize high-quality multi-view HDR images, which has a higher training speed than other learning methods.

We show that the recent breakthrough result of Buchbinder and Feldman [1] could further lead to a deterministic (1 − κ f /e − ε)-approximate algorithm for maximizing a submodular function with curvature κ f under matroid constraint.

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By researching the usual lose problems of field exploration, this paper puts forward and designs an effective personnel help device for tour pal to send help signal to teammates or rescue people. This device comprises a power supply, a temperature and humidity sensor, a GPS positioning, electronic compass, a 433MHz communication module, an OLED display and a micro controller module. This system uses the STM32 series ARM microcontroller with C language programming. It greatly educes the danger coefficient of the field exploration, and the cost of search work of the human, material and financial resources in the field.

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