Showing papers on "High-dynamic-range imaging published in 2008"

Automatic High-Dynamic Range Image Generation for Dynamic Scenes

Abstract: Automatic high-dynamic range image generation from low- dynamic range images offers a solution to conventional methods, which require a static scene. The method consists of two modules: a camera-alignment module and a movement detector, which removes the ghosting effects in the HDRI created by moving objects.

Extending Quality Metrics to Full Luminance Range Images

Abstract: Many quality metrics take as input gamma corrected images and assume that pixel code values are scaled perceptually uniform. Although this is a valid assumption for darker displays operating in the luminance range typical for CRT displays (from 0.1 to 80 cd/m2), it is no longer true for much brighter LCD displays (typically up to 500 cd/m2), plasma displays (small regions up to 1000 cd/m2) and HDR displays (up to 3000 cd/m2). The distortions that are barely visible on dark displays become clearly noticeable when shown on much brighter displays. To estimate quality of images shown on bright displays, we propose a straightforward extension to the popular quality metrics, such as PSNR and SSIM, that makes them capable of handling all luminance levels visible to the human eye without altering their results for typical CRT display luminance levels. Such extended quality metrics can be used to estimate quality of high dynamic range (HDR) images as well as account for display brightness.

Expanding low dynamic range videos for high dynamic range applications

Abstract: In this paper we introduce an algorithm and related methods that expand the contrast range of Low Dynamic Range (LDR) videos in order to regenerate missing High Dynamic Range (HDR) data. For content generated from single exposure LDR sequences, this is clearly an under constrained problem. We achieved the expansion by inverting established tone mapping operator, a process we term inverse tone mapping. This approach is augmented by a number of methods which help expand the luminance for the required pixels while avoiding artifacts. These methods may be used to convert the large libraries of available legacy LDR content for use, for instance, on new content-starved HDR devices. Moreover, these same methods may be used to provide animated emissive surfaces for image based lighting (IBL). We demonstrate results for all the above applications and validate the resultant HDR videos with original HDR references using the HDR Visual Difference Predictor (HDR-VDP) image metric.

Dynamic-range compression and contrast enhancement in infrared imaging systems

Abstract: Third-generation thermal cameras have high dynamic range (up to 14 bits) and collect images that are difficult to visualize because their contrast exceeds the range of traditional display devices. Thus, sophisticated techniques are required to adapt the recorded signal to the display, maintaining, and possibly improving, objects' visibility and image contrast. The problem has already been studied in relation to images acquired in the visible spectral region, while it has been scarcely investigated in the infrared. In this work, this latter subject is addressed, and a new method is presented that combines dynamic-range compression and contrast enhancement techniques to improve the visualization of infrared images. The proposed method is designed to meet typical requirements in infrared sensor applications. The performance is studied through experimental data and compared with that yielded by three well-established algorithms. Evaluation is performed through subjective analysis, assigning each algorithm a score on the basis of the average opinion of human observers. The results demonstrate the effectiveness of the proposed technique in terms of perceptibility of details, edge sharpness, robustness against the horizon effect, and presence of very warm objects.

Gradient-Based Synthesized Multiple Exposure Time Color HDR Image

Abstract: High dynamic range (HDR) of illumination may cause serious distortion and information loss in the viewing and further processing of digital images. On the other hand, digital processing can often improve the visual quality of real-world photographs or views. Recently, HDR imaging techniques have become the focus of much research because of their high theoretical and practical importance. If the scene to be viewed or processed has HDR (dark and bright) illumination, these methods are able to help to detect details that a bright environment washes out, and they miss fewer details in a dark environment. By applying HDR techniques, the performance of different image processing and computer vision algorithms, information enhancement, and object and pattern recognition can also be improved. In this paper, a new tone reproduction algorithm is introduced, which may help to develop hard-to-view or nonviewable features and content of color images. The method applies a multiple exposure time image synthesization technique, where the red, green, and blue (RGB) color components of the pixels are separately handled. In the output, the corresponding (modified) color components are blended. As a result, a high-quality color HDR image is obtained, which contains the maximum level of details and color information.

High Dynamic Range Imaging by Fusing Multiple Raw Images and Tone Reproduction

Abstract: This paper presents an integrated color imaging system for taking images in extremely high dynamic range scenes. The system first fuses several differently exposed raw images to acquire more intensity information. The effective dynamic range of the image raw data can be extended to 256 times if five differently exposed images are fused. Then it runs edge detection iterations to extract the image details in different luminance levels. The proposed tone reproduction algorithm equalizes the histogram of the extracted fine edges which tends to assign larger dynamic range for highly populated regions. Finally, the local contrast enhancement is performed to further refine the image details. The experimental results show that the proposed high dynamic range imaging system has good performance on both tone and color reproduction.

Image sensor with high dynamic range imaging and integrated motion detection

Abstract: This disclosure describes: (1) two different schemes to enhance dynamic range, (2) a new motion detection scheme using in-pixel digital storage, and (3) the motion detection in high illumination for CMOS image sensors. The schemes may be implemented in a small pixel size and easily incorporated in simple column-level circuits for existing CMOS image sensor systems.

Consistent tone reproduction

Abstract: In order to display images of high dynamic range (HDR), tone reproduction operators are usually applied that reduce the dynamic range to that of the display device. Generally, parameters need to be adjusted for each new image to achieve good results. Consistent tone reproduction across different images is therefore difficult to achieve, which is especially true for global operators and to some lesser extent also for local operators. We propose an efficient global tone reproduction method that achieves robust results across a large variety of HDR images without the need to adjust parameters. Consistency and efficiency make our method highly suitable for automated dynamic range compression, which for instance is necessary when a large number of HDR images need to be converted.

Characterization for High Dynamic Range Imaging

Abstract: In this paper we present a new practical camera characterization technique to improve color accuracy in high dynamic range (HDR) imaging. Camera characterization refers to the process of mapping device-dependent signals, such as digital camera RAW images, into a well-defined color space. This is a well-understood process for low dynamic range (LDR) imaging and is part of most digital cameras — usually mapping from the raw camera signal to the sRGB or Adobe RGB color space. This paper presents an efficient and accurate characterization method for high dynamic range imaging that extends previous methods originally designed for LDR imaging. We demonstrate that our characterization method is very accurate even in unknown illumination conditions, effectively turning a digital camera into a measurement device that measures physically accurate radiance values — both in terms of luminance and color — rivaling more expensive measurement instruments.

High dynamic range imaging on mobile devices

Abstract: Natural scenes usually produce radiance maps that have a dynamic range much larger than the dynamic range of the imaging sensors. Due to this fact the captured images, almost always, contain under-exposed and saturated regions. Among several solutions, proposed in the open literature, the multi-frame approaches have been shown to produce high quality results by combining several shots of the same scene, captured at different exposure times. Here we introduce a low complexity multi-frame approach suitable for mobile implementations. We have implemented our method in Symbian OS in a Nokia cameraphone and the results obtained with our proposed system are shown in the paper.

Digital Camera Workflow for High Dynamic Range Images Using a Model of Retinal Processing

Abstract: We propose a complete digital camera workflow to capture and render high dynamic range (HDR) static scenes, from RAW sensor data to an output- referred encoded image. In traditional digital camera processing, demosaicing is one of the first operations done after scene analysis. It is followed by rendering operations, such as color correction and tone mapping. Our approach is based on a model of retinal processing of the human visual system (HVS). In the HVS, rendering operations, including adaptation, are performed directly on the cone responses, which corresponds to a mosaic image. Our workflow conforms more closely to the retinal processing model, performing all rendering before demosaicing.. This reduces the complexity of the computation, as only one third of the pixels are processed. This is especially important as our tone mapping operator applies local and global tone corrections, which is usually needed to well render high dynamic scenes. Our algorithms efficiently process HDR images with different keys and different content.

Multispectral high dynamic range imaging

Abstract: Capturing natural scenes with high dynamic range content using conventional RGB cameras generally results in saturated and underexposed and therefore compromising image areas. Furthermore the image lacks color accuracy due to a systematic color error of the RGB color filters. The problem of the limited dynamic range of the camera has been addressed by high dynamic range imaging1, 2 (HDRI): Several RGB images of different exposures are combined into one image with greater dynamic range. Color accuracy on the other hand can be greatly improved using multispectral cameras,3 which more accurately sample the electromagnetic spectrum. We present a promising combination of both technologies, a high dynamic range multispectral camera featuring a higher color accuracy, an improved signal to noise ratio and greater dynamic range compared to a similar low dynamic range camera.© (2008) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A database of high dynamic range visible and near-infrared multispectral images

Abstract: Simulation of the imaging pipeline is an important tool for the design and evaluation of imaging systems. One of the most important requirements for an accurate simulation tool is the availability of high quality source scenes. The dynamic range of images depends on multiple elements in the imaging pipeline including the sensor, digital signal processor, display device, etc. High dynamic range (HDR) scene spectral information is critical for an accurate analysis of the effect of these elements on the dynamic range of the displayed image. Also, typical digital imaging sensors are sensitive well beyond the visible range of wavelengths. Spectral information with support across the sensitivity range of the imaging sensor is required for the analysis and design of imaging pipeline elements that are affected by IR energy. Although HDR scene data information with visible and infrared content are available from remote sensing resources, there are scarcity of such imagery representing more conventional everyday scenes. In this paper, we address both these issues and present a method to generate a database of HDR images that represent radiance fields in the visible and near-IR range of the spectrum. The proposed method only uses conventional consumer-grade equipment and is very cost-effective.

Two layer scheme for encoding of high dynamic range images

Abstract: With advent of high dynamic range (HDR) imaging techniques, it has been possible to capture natural scenes in larger details. HDR images are tone-mapped to lower dynamic range (LDR) versions for displaying on paper or a screen. Details lost during tone-mapping are important for certain existing and future applications, and need to be preserved. However, the size of HDR images is very large and that gives rise to need of effective encoding techniques. In this paper, we present an encoding scheme for HDR images, which significantly reduces their storage requirements, with a negligible loss of information. We model an HDR image as a piecewise linear function of its tone-mapped version. The tone-mapped image and the error in modeling are stored as LDR images, and these two along with the created model, approximate the HDR image. Comparison with the existing state of the art technique is given to show the effectiveness of our proposed scheme.

Image-splitting techniques for a dual-layer high dynamic range LCD display

Abstract: Liquid crystal displays (LCDs) are replacing analog film in radiology and reducing diagnosis times. Their typical dynamic range, however, can be too low for some applications, and their poor ability to reproduce low-luminance areas represents a critical drawback. The black level of an LCD can be drastically improved by stacking two liquid crystal panels in series. In this way the global transmittance is the pointwise product of the transmittances of the two panels and the theoretical dynamic range is squared. Such a high dynamic range (HDR) display also permits the reproduction of a larger number of gray levels, increasing the bit depth of the device. The two panels, however, are placed at a small distance from each other due to mechanical constraints, and this introduces a parallax error when the display is observed off-axis. A complex, spatially adaptive algorithm is therefore necessary to generate the images used to drive the two panels. We describe the characteristics of a prototype dual-layer HDR display and discuss the issues involved in the image-splitting algorithms. We propose some solutions and analyze their performance, giving a measure of the capabilities and limitations of the device.

Methods to extend the dynamic range of snapshot active pixel sensors

Abstract: The dynamic range of a scene is usually higher than the dynamic range of the sensor used to acquire the image. Design optimizations must be found that increase the intra-scene dynamic range a sensor can achieve. Good dynamic range is necessary to image a scene with the required details and contrast in a single image. The first topic addressed by the paper is the definition of intra-scene dynamic range. The paper will detail past and present techniques to increase the dynamic range of snapshot CMOS image sensors and show the necessary future developments in high dynamic range imaging. The technologies shown are used by various image sensor manufacturers, only a portion thereof are used in Melexis devices.

HDR Imaging From Differently Exposed Multiview Videos

Abstract: A procedure for obtaining high dynamic range (HDR) videos from multiple differently exposed image sequences from a camera array is explored. It is observed that using information along both viewspace (camera) and temporal axes results in a good estimate of the HDR image sequence. Images captured at longer exposures are subject to motion blur. A novel motion deblurring scheme is proposed, prior to the actual HDR mapping process. This involves a multiscale directional structure preservation procedure which uses information from adjacent views along camera-space and frames along time. The proposed deblurring scheme works in spite of illumination variations between images.

Noise in high dynamic range imaging

Abstract: High dynamic range (HDR) imaging is more and more widely used to increase the limited dynamic range of digital cameras and, in turn, to cover the dynamic range of the acquired scene. This image acquisition process can be subdivided into two steps. The first step is the measurement or estimation of the mostly non-linear camera transfer function (CTF). This is followed by the second step, the combination of a set of differently exposed images of the same scene into one HDR image after linearization with the inverse CTF. Each of the individual images in such an exposure set contains noise from the image acquisition process. Consequently, the calculated HDR image will as well contain noise, which fortunately is reduced by the weighted average of the images from the exposure set. We analyze the achieved gain in SNR for different weighting functions proposed in the literature and compare these with a plain average. Although these functions are based on reasonable intuitions, we show that the highest SNRgain is achieved with the plain average.

Real-time photographic local tone reproduction using summed-area tables

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Image splitting techniques for a dual layer high dynamic range LCD display

Abstract: Liquid crystal displays (LCD) are replacing analog film in radiology and permit to reduce diagnosis times. Their typical dynamic range, however, can be too low for some applications, and their poor ability to reproduce low luminance areas represents a critical drawback. The black level of an LCD can be drastically improved by stacking two liquid crystal panels in series. In this way the global transmittance is the pointwise product of the transmittances of the two panels and the theoretical dynamic range is squared. Such a high dynamic range (HDR) display also permits the reproduction of a larger number of gray levels, increasing the bit depth of the device. The two panels, however, are placed at a small distance one from each other due to mechanical constraints, and this introduces a parallax error when the display is observed off-axis. A complex, spatially-adaptive algorithm is therefore necessary to generate the images used to drive the two panels. In this paper, we describe the characteristics of a prototype dual-layer HDR display and discuss the issues involved in the image splitting algorithms. We propose some solutions and analyze their performance, giving a measure of the capabilities and limitations of the device.

High Dynamic Range Image Reconstruction

Abstract: High dynamic range imaging (HDRI) is an emerging field that has the potential to cause a great scientific and technological impact in the near future. Although new, this field is large and complex, with non-trivial relations to many different areas, such as image synthesis, computer vision, video and image processing, digital photography, special effects among others. For the above reasons,HDRI has been extensively researched over the past years and, consequently, the related scientific literature is vast. As an indication that the field is reaching maturity, tutorials and books on HDRI appeared. Moreover, this new resource has already reached interested practitioners in various application areas. In this book, we do not aim at covering the whole field of high dynamic range imaging and its applications, since it is a broad subject that is still evolving. Instead, our intent is to cover the basic principles behind HDRI and focus on one of the currently most important problems, both theoretically and practically. That is, the reconstruction of high dynamic range images from regular low dynamic range pictures. Table of Contents: Introduction / Digital Image / Imaging Devices and Calibration / HDR Reconstruction / HDRI Acquisition and Visualization / Tone Enhancement / References / Biography

Selected Problems of High Dynamic Range Video Compression and GPU-based Contrast Domain Tone Mapping

Abstract: The main goal of High Dynamic Range Imaging (HDRI) is precise reproduction of real world appearance in terms of intensity levels and color gamut at all stages of image and video processing from acquisition to display. In our work, we investigate the problem of lossy HDR image and video compression and provide a number of novel solutions, which are optimized for storage efficiency or backward compatibility with existing compression standards. To take advantage of HDR information even for traditional low-dynamic range displays, we design tone mapping algorithms, which adjust HDR contrast ranges in a scene to those available in typical display devices.

The use of high dynamic range luminance mapping in the assessment, understanding and defining of visual issues in post occupancy building assessment

Abstract: The international focus on embracing daylighting for energy efficient lighting purposes and the corporate sector’s indulgence in the perception of workplace and work practice “transparency” has spurned an increase in highly glazed commercial buildings. This in turn has renewed issues of visual comfort and daylight-derived glare for occupants. In order to ascertain evidence, or predict risk, of these events; appraisals of these complex visual environments require detailed information on the luminances present in an occupant’s field of view. Conventional luminance meters are an expensive and time consuming method of achieving these results. To create a luminance map of an occupant’s visual field using such a meter requires too many individual measurements to be a practical measurement technique. The application of digital cameras as luminance measurement devices has solved this problem. With high dynamic range imaging, a single digital image can be created to provide luminances on a pixel-by-pixel level within the broad field of view afforded by a fish-eye lens: virtually replicating an occupant’s visual field and providing rapid yet detailed luminance information for the entire scene. With proper calibration, relatively inexpensive digital cameras can be successfully applied to the task of luminance measurements, placing them in the realm of tools that any lighting professional should own. This paper discusses how a digital camera can become a luminance measurement device and then presents an analysis of results obtained from post occupancy measurements from building assessments conducted by the Mobile Architecture Built Environment Laboratory (MABEL) project. This discussion leads to the important realisation that the placement of such tools in the hands of lighting professionals internationally will provide new opportunities for the lighting community in terms of research on critical issues in lighting such as daylight glare and visual quality and comfort.

High dynamic range imaging & image-based lighting

Abstract: This class outlines recent advances in high dynamic range imaging (HDRI) - from capture to image-based lighting to display. In a hands-on approach, we show how HDR images and video can be captured, the file formats available to store them, and the algorithms required to prepare them for display on low dynamic range displays. The trade-offs at each step are assessed allowing attendees to make informed choices about data capture techniques, file formats and tone reproduction operators. In addition, the latest developments in image-based lighting will be presented.

The tradeoff between SNR and exposure-set size in HDR imaging

Abstract: In high-dynamic-range (HDR) imaging, a radiance map of a HDR scene can be constructed by capturing the scene multiple times with a digital camera at different exposure settings and then digitally combining the images. As we show in this paper, the signal-to-noise ratio (SNR) of the resulting HDR radiance map depends strongly on the number of images that are captured. We present an analytical model for computing SNR as a function of the set of exposure settings used in image capture and the physical noise parameters of the digital camera. We find that the average dynamic range of the HDR image varies as the inverse of the square-root of the inter-exposure spacing. We also find that using a denser exposure set can significantly reduce the inter-pixel variability and spatial variability of SNR in the final HDR radiance map.

The hopeful future of high dynamic range imaging: invited paper

Abstract: This paper offers an overview of the challenges and opportunities presented by high dynamic range (HDR) imaging. We examine the length of the imaging pipeline, from creation and storage through image editing and viewing, and discuss how each stage is affected by a move to HDR.

A fast and accurate image-based measuring system for isotropic reflection materials

Abstract: We present a novel image-based BRDF (Bidirectional Reflectance Distribution Function) measurement system for materials that have isotropic reflectance properties. Our proposed system is fast due to simple set up and automated operations. It also provides a wide angular coverage and noise reduction capability so that it achieves accuracy that is needed for computer graphics applications. We test the uniformity and constancy of the light source and the reciprocity of the measurement system. We perform a photometric calibration of HDR (High Dynamic Range) camera to recover an accurate radiance map from each HDR image. We verify our proposed system by comparing it with a previous imagebased BRDF measurement system. We demonstrate the efficiency and accuracy of our proposed system by generating photorealistic images of the measured BRDF data that include glossy blue, green plastics, gold coated metal and gold metallic paints.

Auto Exposure Control for Multiple-Slope Cameras

Abstract: The dynamic range of natural scenes usually exceeds the dynamic range of imaging sensors by several orders of magnitude. To overcome information loss multiple-slope cameras allow acquisition of images at extended dynamic ranges. However the response curve still has to be adapted to the scene. We present a new auto exposure control for multiple-slope cameras. The proposed method derives an optimum response curve in terms of recorded information. It considers dynamic range expansion as well as the resulting coarsening of quantization. We evaluated our method by simulation and implementation for an actual multiple-slope camera.

Acceleration of High Dynamic Range Imaging Pipeline Based on Multi-threading and SIMD Technologies

Abstract: In this paper we present a holistic approach to CPU based acceleration of the high dynamic range imaging (HDRI) pipeline. The high dynamic range representation can encode images regardless of the technology used to create and display them, with the accuracy that is only constrained by the limitations of the human eye and not a particular output medium. Unfortunately, the increase in accuracy causes significant computational overhead and effective hardware acceleration is needed to ensure a utility value of HDRI applications. In this work we propose a novel architecture of the HDRI pipeline based on CPU SIMD and multi-threading technologies. We discuss the impact on processing speed caused by vectorization and parallelization of individual image processing operations. A commercial application of the new HDRI pipeline is described together with evaluation of achieved image processing speed-up.

Chromatic coordinates in HDR image coding

Abstract: The paper presents an undertaking to develop most compact high dynamic range image compression format and shows that chromatic color coordinate system plays a central role in such development. Important design considerations, such as conditions and criterions of data accuracy, efficiency and characteristics of color space, are addressed along the way. An additional trade-off between data precision and data size is discussed, and new feature of parameterized precision is introduced. Detailed comparison of Bef, Luv, Yxy chromatic coordinates is performed and special case of color space singularities is analyzed. LinLogBef imaging format implementation is presented and compared against OpenEXR and Radiance HDR formats by compression ratio, relative error and dynamic range characteristics. Other benefits provided by LinLogBef are further discussed, such as the format's convenience for image editing operations.