Academic literature on the topic 'HDR multiple exposures'

The range of light illumination in real scenes is very large, and ordinary cameras can only record a small part of this range, which is far lower than the range of human eyes’ perception of light. High-dynamic range (HDR) imaging technology that has appeared in recent years can record a wider range of illumination than the perceptual range of the human eye. However, the current mainstream HDR imaging technology is to capture multiple low-dynamic range (LDR) images of the same scene with different exposures and then merge them into one HDR image, which greatly increases the amount of data captured. The advent of single-pixel cameras (compressive imaging system) has proved the feasibility of obtaining and restoring image data based on compressive sensing. Therefore, this paper proposes a method for reduced-dimensional capture of high dynamic range images with compressive sensing, which includes algorithms for front end (capturing) and back end (processing). At the front end, the K-SVD dictionary is used to compressive sensing the input multiple-exposure image sequence, thereby reducing the amount of data transmitted to the back end. At the back end, the Orthogonal Matching Pursuit (OMP) algorithm is used to reconstruct the input multiple-exposure image sequence. A low-rank PatchMatch algorithm is proposed to merge the reconstructed image sequence to obtain an HDR image. Simulation results show that, under the premise of reducing the complexity of the front-end equipment and the amount of communication data between the front end and the back end, the overall system achieves a good balance between the amount of calculation and the quality of the HDR image obtained.

The observed luminance of most light sources is many orders of magnitude higher than the luminance of surrounding objects and the background. With the dynamic range of single photographs limited to 8 to 10 bits, both dark and bright values are radically coerced to the limits. This problem is usually circumvented with the use of High-Dynamic-Range (HDR) imaging, assembling multiple photographs of the same scene made at different exposures. But in some situations, or due to equipment limitations, HDR imaging might not be possible. This research is aimed at the extrapolation of luminance peaks within oversaturated Low-Dynamic-Range (LDR) images. The proposed method of extrapolation relies on the identification and analysis of Fraunhofer diffraction patterns created by the aperture. The algorithm is tested on a set of HDR images containing one or two lamps. These images are converted to LDR at a custom saturation cap, then extrapolated to restore the original peaks with relative success.

Camera sensors are physically restricted in the amount of luminance which can be captured at once. To achieve a higher dynamic range, multiple exposures are typically combined. This method comes with several disadvantages, like temporal or alignment aliasing. Hence, we propose a method to preserve high luminance information in a single-shot image. By introducing a grid of highlight preserving pixels, which equals 1% of the total amount of pixels, we are able to sustain information directly incamera for later processing. To provide evidence, that this number of pixels is enough for gaining additional dynamic range, we use a U-Net for reconstruction. For training, we make use of the HDR+ dataset, which we augment to simulate our proposed grid. We demonstrate that our approach can preserve high luminance information, which can be used for a visually convincing reconstruction, close to the ground truth.

AbstractIn the present study, the aim was to investigate the correlation between the acute and habitual dietary intake of flavanones, their main food sources and the concentrations of aglycones naringenin and hesperetin in 24 h urine in a European population. A 24-h dietary recall (24-HDR) and a 24-h urine sample were collected the same day from a subsample of 475 people from four different countries of the European Prospective Investigation into Cancer and Nutrition study. Acute and habitual dietary data were captured through a standardised 24-HDR and a country/centre-specific validated dietary questionnaire (DQ). The intake of dietary flavanones was estimated using the Phenol-Explorer database. Urinary flavanones (naringenin and hesperetin) were analysed using tandem MS with a previous enzymatic hydrolysis. Weak partial correlation coefficients were found between urinary flavanone concentrations and both acute and habitual dietary flavanone intakes (Rpartial = 0·14–0·17). Partial correlations were stronger between urinary excretions and acute intakes of citrus fruit and juices (Rpartial ∼ 0·6) than with habitual intakes of citrus fruit and juices (Rpartial ∼ 0·24). In conclusion, according to our results, urinary excretion of flavanones can be considered a good biomarker of acute citrus intake. However, low associations between habitual flavanone intake and urinary excretion suggest a possible inaccurate estimation of their intake or a too sporadic intake. For assessing habitual exposures, multiple urinary collections may be needed. These results show that none of the approaches tested is ideal, and the use of both DQ and biomarkers can be recommended.

One of the significant qualities of the human vision, which differentiates it from computer vision, is so called attentional control, which is the innate ability of our human eyes to select what visual stimuli to pay attention to at any moment in time. In this sense, the visual salience detection model, which is designed to simulate how the human visual system (HVS) perceives objects and scenes, is widely used for performing multiple vision tasks. This model is also in high demand in the tone mapping technology of high dynamic range images (HDRIs). Another distinct quality of the HVS is that our eyes blink and adjust brightness when objects are in their sight. Likewise, HDR imaging is a technology applied to a camera that takes pictures of an object several times by repeatedly opening and closing a camera iris, which is referred to as multiple exposures. In this way, the computer vision is able to control brightness and depict a range of light intensities. HDRIs are the product of HDR imaging. This article proposes a novel tone mapping method using CCH-based saliency-aware weighting and edge-aware weighting methods to efficiently detect image salience information in the given HDRIs. The two weighting methods combine with a guided filter to generate a modified guided image filter (MGIF). The function of the MGIF is to split an image into the base layer and the detail layer which are the two elements of an image: illumination and reflection, respectively. The base layer is used to obtain global tone mapping and compress the dynamic range of HDRI while preserving the sharp edges of an object in the HDRI. This has a remarkable effect of reducing halos in the resulting HDRIs. The proposed approach in this article also has several distinct advantages of discriminative operation, tolerance to image size variation, and minimized parameter tuning. According to the experimental results, the proposed method has made progress compared to its existing counterparts when it comes to subjective and quantitative qualities, and color reproduction.

Modern imaging applications have increased the demand for High-Definition Range (HDR) imaging. Nonetheless, HDR imaging is not easily available with low-cost imaging sensors, since their dynamic range is rather limited. A viable solution to HDR imaging via low-cost imaging sensors is the synthesis of multiple-exposure images. A low-cost sensor can capture the observed scene at multiple-exposure settings and an image-fusion algorithm can combine all these images to form an increased dynamic range image. In this work, two image-fusion methods are combined to tackle multiple-exposure fusion. The luminance channel is fused using the Mitianoudis and Stathaki (2008) method, while the color channels are combined using the method proposed by Mertens et al. (2007). The proposed fusion algorithm performs well without halo artifacts that exist in other state-of-the-art methods. This paper is an extension version of a conference, with more analysis on the derived method and more experimental results that confirm the validity of the method.

In this study, we develop a real-time high-frame-rate vision system with frame-by-frame automatic exposure (AE) control that can simultaneously synthesize multiple images with different exposure times into a high-dynamic-range (HDR) image for scenarios with dynamic change in illumination. By accelerating the video capture and processing for time-division multithread AE control at the millisecond level, the proposed system can virtually function as multiple AE cameras with different exposure times. This system can capture color HDR images of 512 × 512 pixels in real time at 500 fps by synthesizing four 8-bit color images with different exposure times at consecutive frames, captured at an interval of 2 ms, with pixel-level parallel processing accelerated by a GPU (Graphic Processing Unit) board. Several experimental results for scenarios with a large change in illumination are demonstrated to confirm the performance of the proposed system for real-time HDR imaging.

Abstract The luminous value is high for many natural scenes, which causes loss of information and occurs in dark images. The High Dynamic Range (HDR) technique captures the same objects or scene for multiple times in different exposure and produces the images with proper illumination. This technique is used in the various applications such as medical imaging and observing the skylight, etc. HDR imaging techniques usually have the issue of lower efficiency due to capturing of multiple photos. In this paper, an efficient method is proposed for HDR imaging technique to achieve better performance and lower noise. The Luminance-Chrominance-Gradient High Dynamic Range (LCGHDR) method is proposed to obtain the proper luminous value of images. The same scenario is captured at different exposure are processed by the proposed method. Based on these feature values extracted from the different images and exposure fusion technique was developed that helps for the proper imaging. This experiment was evaluated and analyzed by comparing with the other methods, which showed the efficiency of the proposed method. This method needs only 124.594 seconds for the computation, while existing method need 139.869 seconds for the same number of images.

The limited dynamic range of digital images can be extended by composing different exposures of the same scene to produce HDR images. This thesis is composed of an overview of the state of the art techniques and three methods to tackle the image alignment and deghosting problems in the HDR imaging domain. The first method detects the areas affected by motion, registers the dynamic objects over a reference image, and combines low-dynamic range values to recover HDR values in the whole image. The second approach builds multiscopic HDR images from LDR multi-exposure images. It is based on a patch match algorithm which was adapted and improved to take advantage of epipolar geometry constraints of stereo images. The last method proposes to replace under/over exposed pixels in the reference image by using valid HDR values from other images in the multi-exposure LDR image sequence.
El limitado rango dinámico de las imágenes digitales puede ampliarse mezclando varias imágenes adquiridas con diferentes valores de exposición. Esta tesis incluye un detallado resumen del estado del arte y tres métodos diferentes para alinear las imágenes y corregir el efecto ’ghosting’ en imágenes HDR. El primer método está centrado en detectar las áreas afectadas por el movimiento y registrar los objetos dinámicos sobre una imagen de referencia de modo que se logre recuperar información a lo largo de toda la imagen. Nuestra segunda propuesta es un método para obtener imágenes HDR multiscópicas a partir de diferentes exposiciones LDR. Está basado en un algoritmo de ’patch match’ que ha sido adaptado para aprovechar las ventajas de las restricciones de la geometría epipolar de imágenes estéreo. Por último proponemos reemplazar los píxeles saturados en la imagen de referencia usando valores correctos de otras imágenes de la secuencia.

We describe the design and implementation of a high dynamic range (HDR) imaging system capable of capturing RGB color images with a dynamic range of 10,000,000 : 1 at 25 frames per second. We use a highly programmable camera unit with high throughput A/D conversion, data processing and data output. HDR acquisition is performed by multiple exposures in a continuous rolling shutter progression over the sensor. All the different exposures for one particular row of pixels are acquired head to tail within the frame time, which means that the time disparity between exposures is minimal, the entire frame time can be used for light integration and the longest expo- sure is almost the entire frame time. The system is highly configurable, and trade-offs are possible between dynamic range, precision, number of exposures, image resolution and frame rate.

Master's thesis is focused on capturing of low dynamic range images using common devices such as camera and its multiple exposure. The main part of thesis is dedicated to composing these images to HDR image, inclusive sequence of images of static scenes, but also dynamic ones. Next part describes tone mapping used for display HDR image on LDR monitors. Moreover, there is given design and implementation of application solving problems mentioned earlier. In the end, the implemented application is evaluated and the possible continuation of this work is stated.

碩士
國立成功大學
電腦與通信工程研究所
98
The image captured by the common digital camera, because of the limited of single exposure image, the dynamic range is far lower than the image seen by the human eye. To resolve this issue, the algorithms synthesize images with different exposure to construct a High Dynamic Range Image, HDRI have been invented. These kind of algorithms resolve the issue of the single exposure image with insufficient dynamic range-result in the color far lower than the human eye. However in the algorithms combining images with different exposure, it requires images with different exposure time, and because of the small time difference when capturing the images, the movements of the objects in the picture would result in the Ghost effect. Therefore the method to adjust the moving objects and to eliminate the ghost effect in order to obtain a high resolution and high dynamic range image is a interesting issue. This article uses gradient based synthesized multiple exposure time HDR image as foundation and propose different algorithms to adjust the moving objects and to eliminate the ghost effect. Using histogram maps process to sensor the moving objects, then edge detect to intensify the features of the moving objects to adjust and eliminate the ghost effect. The method would then collaborate with the algorithm of using gradient as foundation to synthesize different exposure images to produce a high dynamic range image. Because the method sensors then adjust the moving object to eliminate the ghost effect, the result of combining different images of high dynamic range image would have a better quality. The evidence suggests that because the adjustment of the moving objects, the ghost effect have been significantly eliminated, thus the algorithm used to produce the high dynamic range image have remarkably improved the quality of the image. Comparing to other algorithms, previous parts of image suffering from the ghost effect are more clear and distinct, and also have a better visual performance in the produced high dynamic range image. Keyword：High dynamic range image(HDRI), histogram, edge detect,ghost,Gassian Blending Function.

Background and purpose: Historically HDR brachytherapy treatment planning systems ignore the transit dose in the computation of patient dose. However, the total radiation dose delivered during each treatment cycle is equal to the sum of the static dose and the transit dose and every HDR application therefore results in two radiation doses. Consequently, the absorbed dose to the target volume is more than the prescribed dose as computed during treatment planning. The aim of this study was to determine the magnitude of the transit dose component of two 192Ir HDR brachytherapy units and assess its dosimetric significance. Materials and Methods: Ionization chamber dosimetry systems (well-type and Farmertype ionization chambers) were used to measure the charge generated during the transit of the 192Ir source from a GammaMed and a Nucletron MicroSelectron HDR afterloader using single catheters of lengths 120 cm. Different source configurations were used for the measurements of integrated charge. Two analysis techniques were used for transit time determination: the multiple exposure technique and the graphical solution of zero exposure. The transit time was measured for the total transit of the radioactive source into (entry) and out of (exit) the catheters. Results: A maximum source transit time of 1.7 s was measured. The transit dose depends on the source activity, source configuration, number of treatment fractions, prescription dose and the type of remote afterloader used. It does not depend on the measurement technique, measurement distance or the analysis technique used for transit time determination. Conclusion: A finite transit time increases the radiation dose beyond that due to the programmed source dwell time alone. The significance of the transit dose would increase with a decrease in source dwell time or a higher activity source.

A cohort study is one in which the outcome (usually disease status) is ascertained for groups of individuals defined on the basis of their exposure. At the time exposure status is determined, all must be free of the disease. All eligible participants are then followed up over time. Since exposure status is determined before the occurrence of the outcome, a cohort study can clarify the temporal sequence between exposure and outcome, with minimal information bias. The historical and the population cohort study (Box 9.1) are efficient variants of the classical cohort study described above, which nevertheless retain the essential components of the cohort study design. The exposure can be dichotomous [i.e. exposed (to obstetric complications at birth) vs. not exposed], or graded as degrees of exposure (e.g. no recent life events, one to two life events, three or more life events). The use of grades of exposure strengthens the results of a cohort study by supporting or refuting the hypothesis that the incidence of the disease increases with increasing exposure to the risk factor; a so-called dose–response relationship. The essential features of a cohort study are: ♦ participants are defined by their exposure status rather than by outcome (as in case–control design); ♦ it is a longitudinal design: exposure status must be ascertained before outcome is known. The classical cohort study In a classical cohort study participants are selected for study on the basis of a single exposure of interest. This might be exposure to a relatively rare occupational exposure, such as ionizing radiation (through working in the nuclear power industry). Care must be taken in selecting the unexposed cohort; perhaps those working in similar industries, but without any exposure to radiation. The outcome in this case might be leukaemia. All those in the exposed and unexposed cohorts would need to be free of leukaemia (hence ‘at risk’) on recruitment into the study. The two cohorts would then be followed up for (say) 10 years and rates at which they develop leukaemia compared directly. Classical cohort studies are rare in psychiatric epidemiology. This may be in part because this type of study is especially suited to occupational exposures, which have previously been relatively little studied as causes of mental illness. However, this may change as the high prevalence of mental disorders in the workplace and their negative impact upon productivity are increasingly recognized. The UK Gulf War Study could be taken as one rather unusual example of the genre (Unwin et al. 1999). Health outcomes, including mental health status, were compared between those who were deployed in the Persian Gulf War in 1990–91, those who were later deployed in Bosnia, and an ‘era control group’ who were serving at the time of the Gulf war but were not deployed. There are two main variations on this classical cohort study design: they are popular as they can, depending on circumstances, be more efficient than the classical cohort design. The population cohort study In the classical cohort study, participants are selected on the basis of exposure, and the hypothesis relates to the effect of this single exposure on a health outcome. However, a large cohort or panel of subjects are sometimes recruited and followed up, often over many years, to study multiple exposures and outcomes. No separate comparison group is required as the comparison group is generally an unexposed sub-group of the panel. Examples include the British Doctor's Study in which over 30,000 British doctors were followed up for over 20 years to study the effects of smoking and other exposures on health (Doll et al. 1994), and the Framingham Heart Study, in which residents of a town in Massachusetts, USA have been followed up for 50 years to study risk factors for coronary heart disease (Wolf et al. 1988). The Whitehall and Whitehall II studies in the UK (Fuhrer et al. 1999; Stansfeld et al. 2002) were based again on an occupationally defined cohort, and have led to important findings concerning workplace conditions and both physical and psychiatric morbidity. Birth cohort studies, in which everyone born within a certain chronological interval are recruited, are another example of this type of study. In birth cohorts, participants are commonly followed up at intervals of 5–10 years. Many recent panel studies in the UK and elsewhere have been funded on condition that investigators archive the data for public access, in order that the dataset might be more fully exploited by the wider academic community. Population cohort studies can test multiple hypotheses, and are far more common than any other type of cohort study. The scope of the study can readily be extended to include mental health outcomes. Thus, both the British Doctor's Study (Doll et al. 2000) and the Framingham Heart Study (Seshadri et al. 2002) have gone on to report on aetiological factors for dementia and Alzheimer's Disease as the cohorts passed into the age groups most at risk for these disorders. A variant of the population cohort study is one in which those who are prevalent cases of the outcome of interest at baseline are also followed up effectively as a separate cohort in order (a) to study the natural history of the disorder by estimating its maintenance (or recovery) rate, and (b) studying risk factors for maintenance (non-recovery) over the follow-up period (Prince et al. 1998). Historical cohort studies In the classical cohort study outcome is ascertained prospectively. Thus, new cases are ascertained over a follow-up period, after the exposure status has been determined. However, it is possible to ascertain both outcome and exposure retrospectively. This variant is referred to as a historical cohort study (Fig. 9.1). A good example is the work of David Barker in testing his low birth weight hypothesis (Barker et al. 1990; Hales et al. 1991). Barker hypothesized that risk for midlife vascular and endocrine disorders would be determined to some extent by the ‘programming’ of the hypothalamo-pituitary axis through foetal growth in utero. Thus ‘small for dates’ babies would have higher blood pressure levels in adult life, and greater risk for type II diabetes (through insulin resistance). A prospective cohort study would have recruited participants at birth, when exposure (birth weight) would be recorded. They would then be followed up over four or five decades to examine the effect of birth weight on the development of hypertension and type II diabetes. Barker took the more elegant (and feasible) approach of identifying hospitals in the UK where several decades previously birth records were meticulously recorded. He then traced the babies as adults (where they still lived in the same area) and measured directly their status with respect to outcome. The ‘prospective’ element of such studies is that exposure was recorded well before outcome even though both were ascertained retrospectively with respect to the timing of the study. The historical cohort study has also proved useful in psychiatric epidemiology where it has been used in particular to test the neurodevelopmental hypothesis for schizophrenia (Jones et al. 1994; Isohanni et al. 2001). Jones et al. studied associations between adult-onset schizophrenia and childhood sociodemographic, neurodevelopmental, cognitive, and behavioural factors in the UK 1946 birth cohort; 5362 people born in the week 3–9 March 1946, and followed up intermittently since then. Subsequent onsets of schizophrenia were identified in three ways: (a) routine data: cohort members were linked to the register of the Mental Health Enquiry for England in which mental health service contacts between 1974 and 1986 were recorded; (b) cohort data: hospital and GP contacts (and the reasons for these contacts) were routinely reported at the intermittent resurveys of the cohort; (c) all cohort participants identified as possible cases of schizophrenia were given a detailed clinical interview (Present State examination) at age 36. Milestones of motor development were reached later in cases than in non-cases, particularly walking. Cases also had more speech problems than had noncases. Low educational test scores at ages 8,11, and 15 years were a risk factor. A preference for solitary play at ages 4 and 6 years predicted schizophrenia. A health visitor's rating of the mother as having below average mothering skills and understanding of her child at age 4 years was a predictor of schizophrenia in that child. Jones concluded ‘differences between children destined to develop schizophrenia as adults and the general population were found across a range of developmental domains. As with some other adult illnesses, the origins of schizophrenia may be found in early life’. Jones' findings were largely confirmed in a very similar historical cohort study in Finland (Isohanni et al. 2001); a 31 year follow-up of the 1966 North Finland birth cohort (n = 12,058). Onsets of schizophrenia were ascertained from a national hospital discharge register. The ages at learning to stand, walk and become potty-trained were each related to subsequent incidence of schizophrenia and other psychoses. Earlier milestones reduced, and later milestones increased, the risk in a linear manner. These developmental effects were not seen for non-psychotic outcomes. The findings support hypotheses regarding psychosis as having a developmental dimension with precursors apparent in early life. There are many conveniences to this approach for the contemporary investigator. ♦ The exposure data has already been collected for you. ♦ The follow-up period has already elapsed. ♦ The design maintains the essential feature of the cohort study, namely that information bias with respect to the assessment of the exposure should not be a problem. ♦ As with the Barker hypothesis example, historical cohort studies are particularly useful for investigating associations across the life course, when there is a long latency between hypothesized exposure and outcome. Despite these important advantages, such retrospective studies are often limited by reliance on historical data that was collected routinely for other purposes; often these data will be inaccurate or incomplete. Also information about possible confounders, such as smoking or diet, may be inadequate.

Analytic studies enable the field epidemiologist to test his or her hypotheses about the source of an outbreak or other health problem. This testing is performed by comparing ill persons’ exposures to those of a comparison group, typically using one of three study types. Cohort studies are used in field investigations when the population affected is well defined and not so large as to preclude collecting data on almost all persons. Case–control studies are commonly used in field investigations because they enable investigators to test multiple hypotheses relatively quickly and inexpensively. Case–case studies, in which the comparison group comprises other patients with the same or similar illness who do not meet the case definition also can be used to rapidly test hypotheses. Although field investigations may be conducted under intense scrutiny and time pressure, be sure to take time to develop hypotheses and carefully design any study.

We thank Professor Merckelbach for his thoughtful commentary, which raises important questions about the treatment of DID and is replete with interesting observations (e.g., DID may represent a complex mood disorder, DID is a severity marker of a polysymptomatic condition, the need to take symptom exaggeration into account in a complete evaluation of DID). For example, Merckelbach questions whether our patient’s DID symptoms could be an example of “spontaneous developing DID, and thereby provide a falsification of the sociocognitive model,” as he presumed we “went to great lengths to avoid the suggestive shaping of DID symptoms.” Shaping influences on patients may be subtle (e.g., exposure to movies, books, magazine misinformation about DID), and symptoms may appear to arise “spontaneously.” Yet in the case of Ms. M., potentially suggestive influences were less than subtle, if not blatant. Indeed, she was not only an avid consumer of media with trauma-based depictions of multiple personalities, but relatively early in her treatment (before SJL came on board), her previous therapist at some point began to interact with supposedly separate personalities, potentially reifying them and rewarding their manifestation....

When encouraging readers of history, we have several broad goals for our students as readers and as learners. We want them to leave their reading with some knowledge of content and to be able to discriminate among ideas for significance, bias, point of view, and perspective. We would like them to think about what they learned and how they learned it, acknowledging the value of talk and others’ opinions and ideas when they are forming their own opinions. We would also hope the study we’ve done would prompt them to ask new questions that lead them to further reading and study. At this stage in their lives, these readers have assumed the reader role of “Text Critic” as they analyze, synthesize, apply, and extend their learning into independent learning and historical expertise. Many of us have enjoyed students who see themselves as historical experts. On Christine’s first day as a social studies teacher, before the bell had rung to allow students to enter class, she encountered her first expert in her new students, Stephen:… “So, you’re going to be my U.S. History teacher. What do you know about Patton?” “Do you mean George Patton from World War II?” “Yes. If you’re going to expect me to learn from you, you better know your World War II stuff. And, you’re going to have to have seen the movie. Have you seen it?” “Well, no. But if you have it . . . “I have it right here with me. Watch it tonight and we can talk about it tomorrow.”… Christine had found her first expert—and her first ally. This is the kind of student we hope we foster as we are planning curriculum and instruction throughout the year. In Ways That Work: Putting Social Studies Standards into Practice, Tarry Lindquist expects these outcomes and plans for them at the beginning of the unit. “Whenever I plan a unit, I first brainstorm ways my students can acquire knowledge, manipulate data, practice skills, and apply their understanding through group activities” (1997, 101). As a result of the time Christine and her students spend working on questioning, thoughtful and careful reading, exposure to multiple texts, and sharing ideas with others, the satisfaction of those goals is evident in her classroom.