In reality, the quality of an image is generally affected by haze. To obtain a well-quality image, removing haze is a hot issue on theory and application. This paper proposes a new algorithm to remove haze of hazy images. In the algorithm, first, the ambient illumination is estimated by a logarithmic guide filtering that can reserve the characteristics of the bright source areas and improve the dark source areas of the hazy image. Second, to overcome the defect of dark channel prior (DCP) and the over-brightness of the bright channel prior (BCP), two models with two parameters are introduced to improve the DCP and BCP, called multi-channel prior method. At the same time, a self-adaptive method is presented to compute the values of the two parameters. At last, based on the multi-channel prior, a self-adaptive method is proposed to compute the transmission mapping value. Further, four classes hazy images are employed to test the proposed method. The experimental results carried out on the public databases demonstrate that the proposed algorithm can outperform the current state-of-the-arts, including more effective defogging, clearer visibility and richer details.INDEX TERMS Remove haze, hazy image, logarithmic guide filtering, multi-channel prior.
New product development is an important driver of sustainable enterprise development. It is necessary to promote the knowledge sharing of heterogeneous individuals such as design, technology, market, and sociologists. This paper discusses the influence of negative individual knowledge management from the perspective of knowledge-sharing hostility and knowledge manipulation on the performance of new product development. To examine our hypotheses, we conducted a questionnaire survey of 438 employees in China. The results show that although knowledge manipulation contributes to individual innovation performance, it has an inverted U-shaped curve relationship with the team's product development performance. The hostility of knowledge sharing induces knowledge manipulation, which indirectly influences the performance of new product development. The coordination flexibility of R&D teams positively moderates the impact of knowledge manipulation on new product development. Implications and future research directions are discussed.
In this paper, we state a combining programming approach to optimize traffic signal control problem. The objective of the model is to minimize the total queue length with weight factors at the end of each phase. Then, modified Twin Gaussian Process (MTGP) is employed to predict the arrival rates for the traffic signal control problem. For achieving automatic control of the traffic signal, an intelligent control method of the traffic signal is proposed in view of the combining method, that is to say, the combining method of MTGP and LP, called MTGPLP, is embraced in the intelligent control system. Furthermore, some numerical experiments are proposed to test the validity of the model and the MTGPLP approach. In particular, the results of numerical experiments show that the model is effective with different arrival rates, departure rates, and weight factors and the combining method is successful.
Captured images are usually influenced by fog or haze. In reality, image dehazing is challenging. This paper proposes a modified artificial multiple-exposure image fusion (AMEF) algorithm to remove the haze from an image. In the algorithm, first, an adaptive gamma-correction transform with the mean and standard deviation values of each component of a hazy image is utilized to verify the intensities. Second, the homomorphic filtering algorithm is introduced into the Gaussian pyramid and Laplacian pyramid to compute the exposed accessible images. Last, a modified Laplacian filter method is presented to calculate the contrast of the exposed accessible images. Further, extensive experimental results demonstrate that the proposed algorithm has superior performance compared with that of some state-of-the-art methods, including higher contrast, richer details and a better visual effect in the dehazed image.INDEX TERMS Image dehazing, adaptive gamma-correction transformation, image fusion, Laplacian pyramid, modified AMEF.
The present study adopted the Pygmalion perspective and a multilevel theoretical framework to investigate whether creative process engagement mediates the linkage of job creativity requirement with employee creativity. We examined whether team knowledge sharing moderates the aforementioned relationship. We obtained data from 71 supervisors and their 453 employees from three companies in China and applied Hierarchical Linear Modeling (HLM) version 6.08 to test the cross-level hypotheses. The results revealed that creative process engagement mediates the positive linkage of job creativity requirement with employee creativity. In addition, we observed that team knowledge sharing moderates the relationship among job creativity requirement, employee creativity, and creative process engagement. The practical and theoretical implications of the findings are discussed.
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