WESPE: Weakly Supervised Photo Enhancer for Digital Cameras

Low-end and compact mobile cameras demonstrate limited photo quality mainly due to space, hardware and budget constraints. In this work, we propose a deep learning solution that translates photos taken by cameras with limited capabilities into DSLR-quality photos automatically. We tackle this problem by introducing a weakly supervised photo enhancer (WESPE) - a novel image-to-image Generative Adversarial Network-based architecture. The proposed model is trained by under weak supervision: unlike previous works, there is no need for strong supervision in the form of a large annotated dataset of aligned original/enhanced photo pairs. The sole requirement is two distinct datasets: one from the source camera, and one composed of arbitrary high-quality images that can be generally crawled from the Internet - the visual content they exhibit may be unrelated. Hence, our solution is repeatable for any camera: collecting the data and training can be achieved in a couple of hours. In this work, we emphasize on extensive evaluation of obtained results. Besides standard objective metrics and subjective user study, we train a virtual rater in the form of a separate CNN that mimics human raters on Flickr data and use this network to get reference scores for both original and enhanced photos. Our experiments on the DPED, KITTI and Cityscapes datasets as well as pictures from several generations of smartphones demonstrate that WESPE produces comparable or improved qualitative results with state-of-the-art strongly supervised methods

Enhancement of dronogram aid to visual interpretation of target objects via intuitionistic fuzzy hesitant sets

In this paper, we address the hesitant information in enhancement task often caused by differences in image contrast. Enhancement approaches generally use certain filters which generate artifacts or are unable to recover all the objects details in images. Typically, the contrast of an image quantifies a unique ratio between the amounts of black and white through a single pixel. However, contrast is better represented by a group of pix- els. We have proposed a novel image enhancement scheme based on intuitionistic hesi- tant fuzzy sets (IHFSs) for drone images (dronogram) to facilitate better interpretations of target objects. First, a given dronogram is divided into foreground and background areas based on an estimated threshold from which the proposed model measures the amount of black/white intensity levels. Next, we fuzzify both of them and determine the hesitant score indicated by the distance between the two areas for each point in the fuzzy plane. Finally, a hyperbolic operator is adopted for each membership grade to improve the pho- tographic quality leading to enhanced results via defuzzification. The proposed method is tested on a large drone image database. Results demonstrate better contrast enhancement, improved visual quality, and better recognition compared to the state-of-the-art methods.Web of Science500866

Low radiation dose in computed tomography: the role of iodine

Recent approaches to reducing radiation exposure during CT examinations typically utilize automated dose modulation strategies on the basis of lower tube voltage combined with iterative reconstruction and other dose-saving techniques. Less clearly appreciated is the potentially substantial role that iodinated contrast media (CM) can play in low-radiation-dose CT examinations. Herein we discuss the role of iodinated CM in low-radiation-dose examinations and describe approaches for the optimization of CM administration protocols to further reduce radiation dose and/or CM dose while maintaining image quality for accurate diagnosis. Similar to the higher iodine attenuation obtained at low-tube-voltage settings, high-iodine-signal protocols may permit radiation dose reduction by permitting a lowering of mAs while maintaining the signal-to-noise ratio. This is particularly feasible in first pass examinations where high iodine signal can be achieved by injecting iodine more rapidly. The combination of low kV and IR can also be used to reduce the iodine dose. Here, in optimum contrast injection protocols, the volume of CM administered rather than the iodine concentration should be reduced, since with high-iodine-concentration CM further reductions of iodine dose are achievable for modern first pass examinations. Moreover, higher concentrations of CM more readily allow reductions of both flow rate and volume, thereby improving the tolerability of contrast administration

Advanced solutions for quality-oriented multimedia broadcasting

Multimedia content is increasingly being delivered via different types of networks to viewers in a variety of locations and contexts using a variety of devices. The ubiquitous nature of multimedia services comes at a cost, however. The successful delivery of multimedia services will require overcoming numerous technological challenges many of which have a direct effect on the quality of the multimedia experience. For example, due to dynamically changing requirements and networking conditions, the delivery of multimedia content has traditionally adopted a best effort approach. However, this approach has often led to the end-user perceived quality of multimedia-based services being negatively affected. Yet the quality of multimedia content is a vital issue for the continued acceptance and proliferation of these services. Indeed, end-users are becoming increasingly quality-aware in their expectations of multimedia experience and demand an ever-widening spectrum of rich multimedia-based services. As a consequence, there is a continuous and extensive research effort, by both industry and academia, to find solutions for improving the quality of multimedia content delivered to the users; as well, international standards bodies, such as the International Telecommunication Union (ITU), are renewing their effort on the standardization of multimedia technologies. There are very different directions in which research has attempted to find solutions in order to improve the quality of the rich media content delivered over various network types. It is in this context that this special issue on broadcast multimedia quality of the IEEE Transactions on Broadcasting illustrates some of these avenues and presents some of the most significant research results obtained by various teams of researchers from many countries. This special issue provides an example, albeit inevitably limited, of the richness and breath of the current research on multimedia broadcasting services. The research i- - ssues addressed in this special issue include, among others, factors that influence user perceived quality, encoding-related quality assessment and control, transmission and coverage-based solutions and objective quality measurements

A Novel Framework for Highlight Reflectance Transformation Imaging

We propose a novel pipeline and related software tools for processing the multi-light image collections (MLICs) acquired in different application contexts to obtain shape and appearance information of captured surfaces, as well as to derive compact relightable representations of them. Our pipeline extends the popular Highlight Reflectance Transformation Imaging (H-RTI) framework, which is widely used in the Cultural Heritage domain. We support, in particular, perspective camera modeling, per-pixel interpolated light direction estimation, as well as light normalization correcting vignetting and uneven non-directional illumination. Furthermore, we propose two novel easy-to-use software tools to simplify all processing steps. The tools, in addition to support easy processing and encoding of pixel data, implement a variety of visualizations, as well as multiple reflectance-model-fitting options. Experimental tests on synthetic and real-world MLICs demonstrate the usefulness of the novel algorithmic framework and the potential benefits of the proposed tools for end-user applications.Terms: "European Union (EU)" & "Horizon 2020" / Action: H2020-EU.3.6.3. - Reflective societies - cultural heritage and European identity / Acronym: Scan4Reco / Grant number: 665091DSURF project (PRIN 2015) funded by the Italian Ministry of University and ResearchSardinian Regional Authorities under projects VIGEC and Vis&VideoLa

Trying to break new ground in aerial archaeology

Aerial reconnaissance continues to be a vital tool for landscape-oriented archaeological research. Although a variety of remote sensing platforms operate within the earth’s atmosphere, the majority of aerial archaeological information is still derived from oblique photographs collected during observer-directed reconnaissance flights, a prospection approach which has dominated archaeological aerial survey for the past century. The resulting highly biased imagery is generally catalogued in sub-optimal (spatial) databases, if at all, after which a small selection of images is orthorectified and interpreted. For decades, this has been the standard approach. Although many innovations, including digital cameras, inertial units, photogrammetry and computer vision algorithms, geographic(al) information systems and computing power have emerged, their potential has not yet been fully exploited in order to re-invent and highly optimise this crucial branch of landscape archaeology. The authors argue that a fundamental change is needed to transform the way aerial archaeologists approach data acquisition and image processing. By addressing the very core concepts of geographically biased aerial archaeological photographs and proposing new imaging technologies, data handling methods and processing procedures, this paper gives a personal opinion on how the methodological components of aerial archaeology, and specifically aerial archaeological photography, should evolve during the next decade if developing a more reliable record of our past is to be our central aim. In this paper, a possible practical solution is illustrated by outlining a turnkey aerial prospection system for total coverage survey together with a semi-automated back-end pipeline that takes care of photograph correction and image enhancement as well as the management and interpretative mapping of the resulting data products. In this way, the proposed system addresses one of many bias issues in archaeological research: the bias we impart to the visual record as a result of selective coverage. While the total coverage approach outlined here may not altogether eliminate survey bias, it can vastly increase the amount of useful information captured during a single reconnaissance flight while mitigating the discriminating effects of observer-based, on-the-fly target selection. Furthermore, the information contained in this paper should make it clear that with current technology it is feasible to do so. This can radically alter the basis for aerial prospection and move landscape archaeology forward, beyond the inherently biased patterns that are currently created by airborne archaeological prospection