Advances in digital camera technology have led to the development of image sensors that are capable of capturing High Dynamic Range (HDR) images. Although this has enabled the capture of greater depths of colour and illumination, there remain problems with regards to transmitting and displaying the HDR image data. Current consumer level displays are designed to only show images with a depth of 8-bits per pixel per channel. Typical HDR images can be 10-bits per pixel per channel and upwards, leading to the first problem, how to display HDR images on Standard Dynamic Range (SDR) displays. This is linked to a further problem, that of transmitting the HDR data to the SDR devices, due to the fact that most state-of-the-art image and video coding standards deal with only SDR data. Further, as with most technologies of this kind, current HDR displays are extremely expensive. Furthermore, media broadcast organisations have invested significant sums of money into their current architecture and are unwilling to completely change their systems at further cost.

Tato diplomová práce se zabývá syntézou HDR obrazu (High Dynamic Range Imaging). HDRI technologie se stala v posledních letech velice populární. Běžný a nejvíce používaný způsob vytvoření HDR obrazu je spojení více snímků stejné scény pořízených pomocí různých expozičních časů. Tato technika funguje správně pouze v případě, že se jedná o statickou scénu. Pokud je však ve scéně nějaký pohyb ve chvíli, kdy se pořizují snímky dané scény, výsledný HDR obraz obsahuje artefakty zvané jako duchy. V této práci jsou prezentovány základní informace o HDRI se zaměřením na metody odstraňující artefakty z HDR obrazů. Práce shrnuje již existující metody a dvě z nich - tzv. bitmap movement detection a histogram based ghost detection - představuje jako vhodné pro použití v real-time skládání HDR obrazu a pro implementaci na FPGA (Field-Programmable Gate Array) architektuře. Tyto metody jsou v práci implementovány v programovacím jazyce C++ jako prototypy. Navíc je zde navržena modifikace metody založené na výpočtu histogramu pro jednodušší a efektivnější implementaci na FPGA architektuře.

Tato práce navrhuje algoritmus pro pořizování ghost-free HDR videa ze sekvence expozic, který je určený pro implementaci ve vestavěných zařízeních. Vlastnosti algoritmu byly ověřeny implementací ve state-of-the-art architektuře HDR kamery, kde je schopen zpracovávat HDR video s potlačením tzv. ghosting efektu rychlostí až 96 snímků za sekundu na FullHD rozlišení, což více než dostačuje pro zpracování v reálném čase. Navrhovaný ghost-free algoritmus produkuje výstup vizuálně srovnatelný s nejmodernějšími algoritmy, které jsou výpočetně řádově složitější a často je nelze na embedded zařízeních ani implementovat.

Made available in DSpace on 2014-06-11T19:24:10Z (GMT). No. of bitstreams: 0 Previous issue date: 2008-02-27Bitstream added on 2014-06-13T19:30:46Z : No. of bitstreams: 1 nascimento_dn_me_bauru_prot.pdf: 3358169 bytes, checksum: 7b167fe8ebd68cbd9073ed5ffb4c7c4d (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / O conforto visual no ambiente de trabalho também é alvo de estudo da ergonomia, e com o auxílio da análise de imagens digitais – HDR (High Dynamic Range) é possível ter um estudo mais rápido e barato contribuindo assim para o bem estar dos trabalhadores, já que uma boa iluminação tornará o ambiente de trabalho mais produtivo e prazeroso. Tem-se por objetivo especificamente, estudar formas de caracterizar o ambiente em relação à possibilidade da ocorrência de ofuscamento a partir de imagens HDR e viabilizar o uso de câmeras fotográficas digitais de uso amador, com lentes padrão, no desenvolvimento de uma sistemática e da correspondente instrumentação para avaliar índices de ofuscamento empregando imagens HDR compostas a partir de fotos obtidas com tais câmeras / The visual comfort in the work environment also is white of study of the ergonomics, and with the aid of the analysis of digital images - HDR (High Dynamic Range) is possible to have a cheap study faster e thus constributing it welfare of the workers, science a good illumination will became the environment of more productive and pleasant work. It is had specifically for objective, to study forms to characterize the environment in relation a possibility da ofuscamento occurrence to leave of images HDR and to make possible the use of digital cameras of amoteur use, with leses standard, no development of a systematics and da corresponding instrumentation to evaluate ofuscamento indices being used composed images HDR to leave of photos gotten with such cameras

The work of this thesis is motivated by the bene t of real-time HDR image processing which helps constructing better seeing aid devices for day-to-day uses. The seeing aids with HDR can achieve dynamic range greater than human eyes to capture visuals under various light conditions. Further, it helps range sensing devices to read the light codes better. This requires realtime HDR image processing running at 24 FPS. In this thesis, we demonstrate implementation of several HDR image compositing and tone mapping methods in CUDA to achieve realtime performance. In addition, a new tone mapping method termed PPEM is introduced as a novel tone mapping method by adjusting per pixel exposure. Finally, we apply relevant HDR methods to range sensing devices for robust reading.

The work of this thesis is motivated by the bene t of real-time HDR image processing which helps constructing better seeing aid devices for day-to-day uses. The seeing aids with HDR can achieve dynamic range greater than human eyes to capture visuals under various light conditions. Further, it helps range sensing devices to read the light codes better. This requires realtime HDR image processing running at 24 FPS. In this thesis, we demonstrate implementation of several HDR image compositing and tone mapping methods in CUDA to achieve realtime performance. In addition, a new tone mapping method termed PPEM is introduced as a novel tone mapping method by adjusting per pixel exposure. Finally, we apply relevant HDR methods to range sensing devices for robust reading.

This report is about how HDR (HighDynamicRange) can be created and used in combination with Tone mapping. This work has been carried out together with Kapsch TrafficCom AB in Jönköping. The objective of this project is to: Evaluate and investigate the effects given to pictures by HDR and tone mapping. Evaluate if the technology may lead to improvements in Kapsch’s systems. To construct a program which is able to handle some form of tone mapping or HDR-algorithm. These questions will be answered in this report: What kind of effects has HDR and tone mapping-algorithms on pictures? Can the HDR-technology give better data in Kapsch’s systems? The research method used in this report is called action research. This means the authors has investigated the technology by reading different documentations and by testing different algorithms to see what kind of result they give. The report describes some of the tests made to see if the technology is appropriate in Kapsch’s system.There is two smaller reports made by the authors which documenting some of the work.The first report describes the work with different settings for a camera to create pictures with HDR-quality. The second report describes the differences between tone mapping-algorithms and different file format. Both reports are included as appendices to this report.In the program created by the authors some larger library’s with standard functions for opening of JPEG-pictures was used. The chosen library’s was MFC and GDI+. The program is developed for a windows environment and handles functions like sharpening with unsharp mask, colour space conversion and tone mapping.

<p>This work centers on digital stack photography and its applications.</p><p>A stack of images refer, in a broader sense, to an ensemble of</p><p>associated images taken with variation in one or more than one various </p><p>values in one or more parameters in system configuration or setting.</p><p>An image stack captures and contains potentially more information than</p><p>any of the constituent images. Digital stack photography (DST)</p><p>techniques explore the rich information to render a synthesized image</p><p>that oversteps the limitation in a digital camera's capabilities.</p><p>This work considers in particular two basic DST problems, which had</p><p>been challenging, and their applications. One is high-dynamic-range</p><p>(HDR) imaging of non-stationary dynamic scenes, in which the stacked</p><p>images vary in exposure conditions. The other</p><p>is large scale panorama composition from multiple images. In this</p><p>case, the image components are related to each other by the spatial</p><p>relation among the subdomains of the same scene they covered and</p><p>captured jointly. We consider the non-conventional, practical and</p><p>challenge situations where the spatial overlap among the sub-images is</p><p>sparse (S), irregular in geometry and imprecise from the designed</p><p>geometry (I), and the captured data over the overlap zones are noisy</p><p>(N) or lack of features. We refer to these conditions simply as the</p><p>S.I.N. conditions.</p><p>There are common challenging issues with both problems. For example,</p><p>both faced the dominant problem with image alignment for</p><p>seamless and artifact-free image composition. Our solutions to the</p><p>common problems are manifested differently in each of the particular</p><p>problems, as a result of adaption to the specific properties in each</p><p>type of image ensembles. For the exposure stack, existing</p><p>alignment approaches struggled to overcome three main challenges:</p><p>inconsistency in brightness, large displacement in dynamic scene and</p><p>pixel saturation. We exploit solutions in the following three</p><p>aspects. In the first, we introduce a model that addresses and admits</p><p>changes in both geometric configurations and optical conditions, while</p><p>following the traditional optical flow description. Previous models</p><p>treated these two types of changes one or the other, namely, with</p><p>mutual exclusions. Next, we extend the pixel-based optical flow model</p><p>to a patch-based model. There are two-fold advantages. A patch has</p><p>texture and local content that individual pixels fail to present. It</p><p>also renders opportunities for faster processing, such as via</p><p>two-scale or multiple-scale processing. The extended model is then</p><p>solved efficiently with an EM-like algorithm, which is reliable in the</p><p>presence of large displacement. Thirdly, we present a generative</p><p>model for reducing or eliminating typical artifacts as a side effect</p><p>of an inadequate alignment for clipped pixels. A patch-based texture</p><p>synthesis is combined with the patch-based alignment to achieve an</p><p>artifact free result.</p><p>For large-scale panorama composition under the S.I.N. conditions, we</p><p>have developed an effective solution scheme that significantly reduces</p><p>both processing time and artifacts. Previously existing approaches can</p><p>be roughly categorized as either geometry-based composition or feature</p><p>based composition. In the former approach, one relies on precise</p><p>knowledge of the system geometry, by design and/or calibration. It</p><p>works well with a far-away scene, in which case there is only limited</p><p>variation in projective geometry among the sub-images. However, the</p><p>system geometry is not invariant to physical conditions such as</p><p>thermal variation, stress variation and etc.. The composition with</p><p>this approach is typically done in the spatial space. The other</p><p>approach is more robust to geometric and optical conditions. It works</p><p>surprisingly well with feature-rich and stationary scenes, not well</p><p>with the absence of recognizable features. The composition based on</p><p>feature matching is typically done in the spatial gradient domain. In</p><p>short, both approaches are challenged by the S.I.N. conditions. With</p><p>certain snapshot data sets obtained and contributed by Brady et al, </p><p>these methods either fail in composition or render images with</p><p>visually disturbing artifacts. To overcome the S.I.N. conditions, we</p><p>have reconciled these two approaches and made successful and</p><p>complementary use of both priori and approximate information about</p><p>geometric system configuration and the feature information from the</p><p>image data. We also designed and developed a software architecture</p><p>with careful extraction of primitive function modules that can be</p><p>efficiently implemented and executed in parallel. In addition to a</p><p>much faster processing speed, the resulting images are clear and</p><p>sharper at the overlapping zones, without typical ghosting artifacts.</p> / Dissertation

Digital photography became widespread with the global use of smartphones. However, most of the captured images do not fully use the camera capabilities by storing the captured photos in a format with limited dynamic range. The subject of dynamic range expansion and reconstruction has been researched since early 2000s and recently gave rise to several new reconstruction methods using convolutional neural networks (CNNs), whose performance has not yet been comprehensively compared. By implementing and using our dynamic range reconstruction evaluation framework we compare the reconstruction quality of individual CNN-based approaches. We also implement a mobile HDR camera application and evaluate the feasibility of running the best-performing reconstruction method directly on a mobile device.

No description available.