Fully-automatic inverse tone mapping algorithm based on dynamic mid-level tone mapping

High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show LDR content on HDR displays, it needs to be up-scaled using a so-called inverse tone mapping algorithm. Several techniques for inverse tone mapping have been proposed in the last years, going from simple approaches based on global and local operators to more advanced algorithms such as neural networks. Some of the drawbacks of existing techniques for inverse tone mapping are the need for human intervention, the high computation time for more advanced algorithms, limited low peak brightness, and the lack of the preservation of the artistic intentions. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping capable of real-time video processing. Our proposed algorithm allows expanding LDR images into HDR images with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using the full-reference objective quality metrics HDR-VDP-2.2 and DRIM, and carrying out a subjective pair-wise comparison experiment. We compared our results with those obtained with the most recent methods found in the literature. Experimental results demonstrate that our proposed method outperforms the current state-of-the-art of simple inverse tone mapping methods and its performance is similar to other more complex and time-consuming advanced techniques

Colour constancy using von Kries transformations: colour constancy "goes to the Lab"

Colour constancy algorithms aim at correcting colour towards a correct perception within scenes. To achieve this goal they estimate a white point (the illuminant's colour), and correct the scene for its in uence. In contrast, colour management performs on input images colour transformations according to a pre-established input pro le (ICC pro le) for the given con- stellation of input device (camera) and conditions (illumination situation). The latter case presents a much more analytic approach (it is not based on an estimation), and is based on solid colour science and current industry best practises, but it is rather in exible towards cases with altered conditions or capturing devices. The idea as outlined in this paper is to take up the idea of working on visually linearised and device independent CIE colour spaces as used in colour management, and to try to apply them in the eld of colour constancy. For this purpose two of the most well known colour constancy algorithms White Patch Retinex and Grey World Assumption have been ported to also work on colours in the CIE LAB colour space. Barnard's popular benchmarking set of imagery was corrected with the original imple- mentations as a reference and the modi ed algorithms. The results appeared to be promising, but they also revealed strengths and weaknesses

Automated Home Oxygen Delivery for Patients with COPD and Respiratory Failure: A New Approach

Long-term oxygen therapy (LTOT) has become standard care for the treatment of patients with chronic obstructive pulmonary disease (COPD) and other severe hypoxemic lung diseases. The use of new portable O-2 concentrators (POC) in LTOT is being expanded. However, the issue of oxygen titration is not always properly addressed, since POCs rely on proper use by patients. The robustness of algorithms and the limited reliability of current oximetry sensors are hindering the effectiveness of new approaches to closed-loop POCs based on the feedback of blood oxygen saturation. In this study, a novel intelligent portable oxygen concentrator (iPOC) is described. The presented iPOC is capable of adjusting the O-2 flow automatically by real-time classifying the intensity of a patient's physical activity (PA). It was designed with a group of patients with COPD and stable chronic respiratory failure. The technical pilot test showed a weighted accuracy of 91.1% in updating the O-2 flow automatically according to medical prescriptions, and a general improvement in oxygenation compared to conventional POCs. In addition, the usability achieved was high, which indicated a significant degree of user satisfaction. This iPOC may have important benefits, including improved oxygenation, increased compliance with therapy recommendations, and the promotion of PA

Final Report of the DAUFIN project

DAUFIN = Data Assimulation within Unifying Framework for Improved river basiN modeling (EC 5th framework Project

Objectives, stimulus and feedback in signal control of road traffic

This article identifies the prospective role of a range of intelligent transport systems technologies for the signal control of road traffic. We discuss signal control within the context of traffic management and control in urban road networks and then present a control-theoretic formulation for it that distinguishes the various roles of detector data, objectives of optimization, and control feedback. By reference to this, we discuss the importance of different kinds of variability in traffic flows and review the state of knowledge in respect of control in the presence of different combinations of them. In light of this formulation and review, we identify a range of important possibilities for contributions to traffic management and control through traffic measurement and detection technology, and contemporary flexible optimization techniques that use various kinds of automated learning

Historical forest biomass dynamics modelled with Landsat spectral trajectories

Acknowledgements National Forest Inventory data are available online, provided by Ministerio de Agricultura, Alimentación y Medio Ambiente (España). Landsat images are available online, provided by the USGS.Peer reviewedPostprin

Evaluation of the color image and video processing chain and visual quality management for consumer systems

With the advent of novel digital display technologies, color processing is increasingly becoming a key aspect in consumer video applications. Today’s state-of-the-art displays require sophisticated color and image reproduction techniques in order to achieve larger screen size, higher luminance and higher resolution than ever before. However, from color science perspective, there are clearly opportunities for improvement in the color reproduction capabilities of various emerging and conventional display technologies. This research seeks to identify potential areas for improvement in color processing in a video processing chain. As part of this research, various processes involved in a typical video processing chain in consumer video applications were reviewed. Several published color and contrast enhancement algorithms were evaluated, and a novel algorithm was developed to enhance color and contrast in images and videos in an effective and coordinated manner. Further, a psychophysical technique was developed and implemented for performing visual evaluation of color image and consumer video quality. Based on the performance analysis and visual experiments involving various algorithms, guidelines were proposed for the development of an effective color and contrast enhancement method for images and video applications. It is hoped that the knowledge gained from this research will help build a better understanding of color processing and color quality management methods in consumer video