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Multi-exposure fusion (MEF) is a technique that combines different snapshots of the same scene, captured with different exposure times, into a single image. This combination process (also known as fusion) is performed in such a way that the parts with better exposure of each input image have a stronger influence. Therefore, in the result image all areas are well exposed. In this paper, we propose a new method that performs MEF and noise removal. Rather than denoising each input image individually and then fusing the obtained results, the proposed strategy jointly performs fusion and denoising in the Discrete Cosinus Transform (DCT) domain, which leads to a very efficient algorithm. The method takes advantage of spatio-temporal patch selection and collaborative 3D thresholding. Several experiments show that the obtained results are significantly superior to the existing state of the art. [ABSTRACT FROM AUTHOR]

This paper presents an overview of the most cited papers in all the journals indexed in the Web of Science in the tourism, leisure and hospitality fields through a bibliometric approach. The paper presents several lists with the most cited papers and the publication and citation structure of the last decades in the tourism, leisure and hospitality fields. It also analyzes how the main topics and keywords have changed in these areas in order to raise awareness of the topics and keywords that will predominate in the research in these fields over the next years. [ABSTRACT FROM AUTHOR]