Showing papers on "High-dynamic-range imaging published in 2009"

Artifact-free High Dynamic Range imaging

Abstract: The contrast in real world scenes is often beyond what consumer cameras can capture. For these situations, High Dynamic Range (HDR) images can be generated by taking multiple exposures of the same scene. When fusing information from different images, however, the slightest change in the scene can generate artifacts which dramatically limit the potential of this solution. We present a technique capable of dealing with a large amount of movement in the scene: we find, in all the available exposures, patches consistent with a reference image previously selected from the stack. We generate the HDR image by averaging the radiance estimates of all such regions and we compensate for camera calibration errors by removing potential seams. We show that our method works even in cases when many moving objects cover large regions of the scene.

Bilateral Filter Based Compositing for Variable Exposure Photography

Abstract: Compositing a scene from multiple images is of considerableinterest to graphics professionals. Typical compositing techniques involve estimation or explicit prepar ation of matte by an artist. In this article, we address the problem of automatic compositing of a scene from images o btained through variable exposure photography. We consider the High Dynamic Range Imaging (HDRI) problem an d review some of the existing approaches for directly generating a Low Dynamic Range (LDR) image from mul ti-exposure images. We propose a computationally efficient method of scene compositing using edge-prese rving filters such as bilateral filters. The key challenge is to composite the multi-exposure images in such a way so as t o preserve details in both brightly and poorly illuminated regions of the scene within the limited dynamicrange.

High dynamic range scanning technique

Abstract: Measuring objects with a high variation range of surface reflectivity is challenging for any optical method: This paper addresses a high dynamic range scanning technique that can measure this type of object. It takes advantage of one merit of a phase-shifting algorithm: pixel-by-pixel phase retrieval. For each measurement, a sequence of fringe images with different exposures are taken: the brightest ones have good fringe quality in the darkest areas while the darkest ones have good fringe quality in the brightest areas. They are arranged from brighter to darker (i.e., from higher exposure to lower exposure). The final fringe images, used for phase retrieval, are produced pixel-by-pixel by choosing the brightest but unsaturated corresponding pixel from one exposure. A phase-shifting algorithm is employed to compute the phase, which can be further converted to coordinates. Our experiments demonstrate that the proposed technique can successfully measure objects with high dynamic range of surface reflectivity variation.

Evaluation of reverse tone mapping through varying exposure conditions

Abstract: Most existing image content has low dynamic range (LDR), which necessitates effective methods to display such legacy content on high dynamic range (HDR) devices. Reverse tone mapping operators (rTMOs) aim to take LDR content as input and adjust the contrast intelligently to yield output that recreates the HDR experience. In this paper we show that current rTMO approaches fall short when the input image is not exposed properly. More specifically, we report a series of perceptual experiments using a Brightside HDR display and show that, while existing rTMOs perform well for under-exposed input data, the perceived quality degrades substantially with over-exposure, to the extent that in some cases subjects prefer the LDR originals to images that have been treated with rTMOs. We show that, in these cases, a simple rTMO based on gamma expansion avoids the errors introduced by other methods, and propose a method to automatically set a suitable gamma value for each image, based on the image key and empirical data. We validate the results both by means of perceptual experiments and using a recent image quality metric, and show that this approach enhances visible details without causing artifacts in incorrectly-exposed regions. Additionally, we perform another set of experiments which suggest that spatial artifacts introduced by rTMOs are more disturbing than inaccuracies in the expanded intensities. Together, these findings suggest that when the quality of the input data is unknown, reverse tone mapping should be handled with simple, non-aggressive methods to achieve the desired effect.

Self-coherent camera as a focal plane wavefront sensor: simulations

Abstract: Direct detection of exoplanets requires high dynamic range imaging. Coronagraphs could be the solution, but their performance in space is limited by wavefront errors (manufacturing errors on optics, temperature variations, etc.), which create quasi-static stellar speckles in the final image. Several solutions have been suggested for tackling this speckle noise. Differential imaging techniques substract a reference image to the coronagraphic residue in a post-processing imaging. Other techniques attempt to actively correct wavefront errors using a deformable mirror. In that case, wavefront aberrations have to be measured in the science image to extremely high accuracy. We propose the self-coherent camera sequentially used as a focal-plane wavefront sensor for active correction and differential imaging. For both uses, stellar speckles are spatially encoded in the science image so that differential aberrations are strongly minimized. The encoding is based on the principle of light incoherence between the hosting star and its environment. In this paper, we first discuss one intrinsic limitation of deformable mirrors. Then, several parameters of the self-coherent camera are studied in detail. We also propose an easy and robust design to associate the self-coherent camera with a coronagraph that uses a Lyot stop. Finally, we discuss the case of the association with a four-quadrant phase mask and numerically demonstrate that such a device enables the detection of Earth-like planets under realistic conditions. The parametric study of the technique lets us believe it can be implemented quite easily in future instruments dedicated to direct imaging of exoplanets.

New technique for the visualization of high dynamic range infrared images

Abstract: We propose a new dynamic range compression technique for infrared (IR) imaging systems that enhances details visibility and allows the control and adjustment of the image appearance by setting a number of tunable parameters. This technique adopts a bilateral filter to extract a details component and a coarse component. The two components are processed independently and then recombined to obtain the output-enhanced image that fits the display dynamic range. The contribution made is threefold. We propose a new technique for the visualization of high dynamic range (HDR) images that is specifically tailored to IR images. We show the effectiveness of the method by analyzing experimental IR images that represent typical area surveillance and object recognition applications. Last, we quantitatively assess the performance of the proposed technique, comparing the quality of the enhanced image with that obtained through two well-established visualization methods.

High dynamic range imaging for stereoscopic scene representation

Abstract: This paper presents a method for generating high dynamic range and disparity images by simultaneously capturing the high and low exposure images using a pair of cameras. The proposed stereoscopic high dynamic range imaging technique is able to record multiple exposures without any time delay, and thus suitable for high dynamic range video synthesis. We have demonstrated that it is possible to construct the camera response function using a pair of images with different amount of exposure. The intensities of the stereo images can then be normalized for correspondence matching. Experiments using the Middlebury stereo datasets are presented.

A psychophysical evaluation of inverse tone mapping techniques

Abstract: In recent years inverse tone mapping techniques have been proposed for enhancing low-dynamic range (LDR) content for a high-dynamic range (HDR) experience on HDR displays, and for image based lighting. In this paper, we present a psychophysical study to evaluate the performance of inverse (reverse) tone mapping algorithms. Some of these techniques are computationally expensive because they need to resolve quantization problems that can occur when expanding an LDR image. Even if they can be implemented efficiently on hardware, the computational cost can still be high. An alternative is to utilize less complex operators; although these may suffer in terms of accuracy. Our study investigates, firstly, if a high level of complexity is needed for inverse tone mapping and, secondly, if a correlation exists between image content and quality. Two main applications have been considered: visualization on an HDR monitor and image-based lighting.

Image reconstruction in the gigavision camera

Abstract: Recently we have proposed a new image device called the gigavision camera. The main feature of this camera is that the pixels have a binary response. The response function of a gigavision sensor is non-linear and similar to a logarithmic function, which makes the camera suitable for high dynamic range imaging. Since the sensor can detect a single photon, the camera is very sensitive and can be used for night vision and astronomical imaging. One important aspect of the gigavision camera is how to estimate the light intensity through binary observations. We model the light intensity field as 2D piecewise constant and use Maximum Penalized Likelihood Estimation (MPLE) to recover it. Dynamic programming is used to solve the optimization problem. Due to the complex computation of dynamic programming, greedy algorithm and pruning quadtrees are proposed. They show acceptable reconstruction performance with low computational complexity. Experimental results with synthesized images and real images taken by a single-photon avalanche diode (SPAD) camera are given.

Method and apparatus for motion artifact removal in multiple-exposure high-dynamic range imaging

Abstract: Methods and apparatuses for correcting image artifacts in a high dynamic range image formed by combining a plurality of exposures taken at different integration periods. A determination is made as to whether there is motion between the exposures. If motion is detected, pixel signal values chosen are replaced with pixel signal values from another exposure.

High Dynamic Range Imaging and Low Dynamic Range Expansion for Generating HDR Content.

Abstract: In the last few years, researchers in the field of High Dynamic Range (HDR) Imaging have focused on providing tools for expanding Low Dynamic Range (LDR) content for the generation of HDR images due to the growing popularity of HDR in applications, such as photography and rendering via Image-Based Lighting, and the imminent arrival of HDR displays to the consumer market. LDR content expansion is required due to the lack of fast and reliable consumer level HDR capture for still images and videos. Furthermore, LDR content expansion, will allow the re-use of legacy LDR stills, videos and LDR applications created, over the last century and more, to be widely available. The use of certain LDR expansion methods, those that are based on the inversion of Tone Mapping Operators (TMOs), has made it possible to create novel compression algorithms that tackle the problem of the size of HDR content storage, which remains one of the major obstacles to be overcome for the adoption of HDR. These methods are used in conjunction with traditional LDR compression methods and can evolve accordingly. The goal of this report is to provide a comprehensive overview on HDR Imaging, and an in depth review on these emerging topics.

Backlight simulation at reduced resolutions to determine spatial modulation of light for high dynamic range images

Abstract: Embodiments of the invention relate generally to generating images with an enhanced range of brightness levels, and more particularly, to facilitating high dynamic range imaging by adjusting pixel data and/or using predicted values of luminance, for example, at different resolutions. In at least one embodiment, a method generates an image with an enhanced range of brightness levels. The method can include accessing a model of backlight that includes data representing values of luminance for a number of first samples. The method also can include inverting the values of luminance, as well as upsampling inverted values of luminance to determine upsampled values of luminance. Further, the method can include scaling pixel data for a number of second samples by the upsampled values of luminance to control a modulator to generate an image.

Transmission illuminance proxy HDR imaging: A new technique to quantify luminous flux.

Abstract: A technique to measure arbitrarily complex luminous fluxes across large areas is presented. The technique is founded on high-dynamic range (HDR) imaging technology and can be achieved using a standard consumer digital camera and everyday materials such as printer-grade white paper. The same approach can also be used to determine the direct and diffuse components of illuminance. The technique has been named transmission illuminance proxy - high dynamic range imaging or TIP-HDRI.

Systems and methods for noise reduction in high dynamic range imaging

Abstract: This is generally directed to systems and methods for noise reduction in high dynamic range (“HDR”) imaging systems. In some embodiments, multiple images of the same scene can be captured, where each of the images is exposed for a different amount of time. An HDR image may be created by suitably combining the images. However, the signal-to-noise ratio (“SNR”) curve of the resulting HDR image can have discontinuities in sections of the SNR curve corresponding to shifts between different exposure times. Accordingly, in some embodiments, a noise model for the HDR image can be created that takes into account these discontinuities in the SNR curve. For example, a noise model can be created that smoothes the discontinuities of the SNR curve into a continuous function. This noise model may then be used with a Bayer Filter or any other suitable noise filter to remove noise from the HDR image.

Exposure fusion based on steerable pyramid for displaying high dynamic range scenes

Abstract: Currently, most exposure fusion algorithms are put forward on the assumption that the source images are aligned prior to fusion. As a result, some artifacts, such as haloing, may be caused due to the slight misalignment in the source images. In order to reduce the influence induced by the misalignment, a novel shift-invariant and rotation-invariant steerable pyramid-based exposure fusion (SPBEF) algorithm is proposed. It can combine multiple color images of a scene with different exposures to one image with high quality. First, instead of processing of R, G, and B channels separately, the chrominance information of the scene is obtained by the average image of the median two images. The strategy can greatly reduce the computational complexity. Second, the luminance images of source images are then transferred to frequency domain and are fused to one luminance image using different fusion rules in different frequencies. In this process, fusion is performed in a hierarchical fashion. Last, the final color image is generated by combining the data of the fused luminance image and the chrominance information. Experiments show that SPBEF can give comparative or even better results compared to other exposure fusion algorithms, as well as other traditional pyramid-based fusion algorithms.

Piecewise tone reproduction for high dynamic range imaging

Abstract: To display high dynamic range (HDR) images onto conventional displayable devices that have low dynamic range (LDR) such as monitors and printers, we propose a piecewise tone reproduction operator with chromatic adaptation. The strong point of our operator is to reproduce displayable LDR images while maintaining a perceptual match between the real world and the displayed image. The algorithm for dynamic range reduction relies on piecewise constructs and suitable tone reproduction functions that depend on the estimations of global luminance modification and local luminance adaptation. Combined with dynamic range reduction, the proposed algorithm also applies the chromatic adaptation technique of the color appearance model in order to preserve the chromatic appearance and color consistency across scene and display environments. The experimental results show that the proposed algorithm achieves good subjective results while preserving details of the image. Furthermore, the proposed algorithm has a fast, simple and practical structure for implementation.

Lossy Compression of Floating Point High Dynamic Range Images Using JPEG2000

Abstract: In recent years, a new technique called High Dynamic Range (HDR) has gained attention in the image processing field. By representing pixel values with floating point numbers, recorded images can hold significantly more luminance information than ordinary integer images. This paper focuses on the realization of a lossy compression scheme for HDR images. The JPEG2000 standard is used as a basic component and is efficiently integrated into the compression chain. Based on a detailed analysis of the floating point format and the human visual system, a concept for lossy compression is worked out and thoroughly optimized. Our scheme outperforms all other existing lossy HDR compression schemes and shows superior performance both at low and high bitrates.

Nonlinear mapping of the luminance in dual-layer high dynamic range displays

Abstract: It has long been known that the human visual system (HVS) has a nonlinear response to luminance. This nonlinearity can be quantified using the concept of just noticeable difference (JND), which represents the minimum amplitude of a specified test pattern an average observer can discern from a uniform background. The JND depends on the background luminance following a threshold versus intensity (TVI) function. It is possible to define a curve which maps physical luminances into a perceptually linearized domain. This mapping can be used to optimize a digital encoding, by minimizing the visibility of quantization noise. It is also commonly used in medical applications to display images adapting to the characteristics of the display device. High dynamic range (HDR) displays, which are beginning to appear on the market, can display luminance levels outside the range in which most standard mapping curves are defined. In particular, dual-layer LCD displays are able to extend the gamut of luminance offered by conventional liquid crystals towards the black region; in such areas suitable and HVS-compliant luminance transformations need to be determined. In this paper we propose a method, which is primarily targeted to the extension of the DICOM curve used in medical imaging, but also has a more general application. The method can be modified in order to compensate for the ambient light, which can be significantly greater than the black level of an HDR display and consequently reduce the visibility of the details in dark areas.

Chromatic adaptation-based tone reproduction for high-dynamic-range imaging

Abstract: We present an adaptive tone reproduction algorithm for displaying high-dynamic-range (HDR) images on conventional low-dynamic-range (LDR) display devices. The proposed algorithm consists of an adaptive tone reproduction operator and chromatic adaptation. The algorithm for dynamic range reduction relies on suitable tone reproduction functions that depend on histogram-based parameter estimation to adjust luminance according to global and local features. Instead of relying only on reduction of dynamic range, this chromatic adaption technique also preserves chromatic appearance and color consistency across scene and display environments. Our experimental results demonstrate that the proposed algorithm achieves good subjective quality while preserving image details. Furthermore, the proposed algorithm is simple and practical for implementation.

Optical-digital correlator with increased dynamic range using spatially varying pixels exposure technique

Abstract: In this work the application of the spatially varying pixels exposure technique for obtaining linear high dynamic range (HDR) images of correlation signals by Bayer-covered photo sensors is presented. Bayer colour filters array is considered as an array of attenuating filters in the quasimonochromatic light. The procedure of HDR images reconstruction using data from neighbour pixels and preliminary obtained correction coefficients is described. Experimental results of HDR registration of correlation signals are provided. It is shown that reconstructed HDR correlation signals are linear as normal signals are. The increase of dynamic range of signal’s registration from 58 dB up to 73 dB is obtained. Results on recognition of test objects with normal and HDR registration are discussed.

Image registration for multi-exposed HDRI and motion deblurring

Abstract: In multi-exposure based image fusion task, alignment is an essential prerequisite to prevent ghost artifact after blending. Compared to usual matching problem, registration is more difficult when each image is captured under different photographing conditions. In HDR imaging, we use long and short exposure images, which have different brightness and there exist over/under satuated regions. In motion deblurring problem, we use blurred and noisy image pair and the amount of motion blur varies from one image to another due to the different exposure times. The main difficulty is that luminance levels of the two images are not in linear relationship and we cannot perfectly equalize or normalize the brightness of each image and this leads to unstable and inaccurate alignment results. To solve this problem, we applied probabilistic measure such as mutual information to represent similarity between images after alignment. In this paper, we discribed about the characteristics of multi-exposed input images in the aspect of registration and also analyzed the magnitude of camera hand shake. By exploiting the independence of luminance of mutual information, we proposed a fast and practically useful image registration technique in multiple capturing. Our algorithm can be applied to extreme HDR scenes and motion blurred scenes with over 90% success rate and its simplicity enables to be embedded in digital camera and mobile camera phone. The effectiveness of our registration algorithm is examined by various experiments on real HDR or motion deblurring cases using hand-held camera.

Calibration and imaging challenges at low radio frequencies: An overview of the state of the art

Abstract: Many scientific deliverables of the next generation low frequency radio telescopes require high dynamic range imaging. Next generation telescopes under construction indeed promise at least a ten-fold increase in the sensitivity compared with existing telescopes. The projected achievable RMS noise in the images from these telescopes is in the range of 1--10$\mu$Jy/beam corresponding to typical imaging dynamic ranges of $10^{6-7}$. High imaging dynamic range require removal of systematic errors to high accuracy and for long integration intervals. In general, many source of errors are directionally dependent and unless corrected for, will be a limiting factor for the imaging dynamic range of these next generation telescopes. This requires development of new algorithms and software for calibration and imaging which can correct for such direction and time dependent errors. In this paper, I discuss the resulting algorithmic and computing challenges and the recent progress made towards addressing these challenges.

Locally adaptive high range image reproduction inspired by human visual system

Abstract: Dynamic range of natural scenes that we see in daily life ranges up to 120dB. Unfortunately, typical imaging devices only cover about 50dB without any special circuit technique. To overcome this dynamic range problem, many algorithms and devices have been developed and commercialized. However, commercialization in the field where image quality is emphasized is not as active as in the filed where the image information is emphasized. This is because there are still some limitations in capturing and displaying high dynamic range (HDR) image without loss of image information (color, edge and contrast, etc.) In displaying HDR image, some losses of image information during tone reproduction are inevitable, since the HDR image have to be processed with some kind of tone reproduction method to compress the dynamic range fit to the low dynamic range (LDR) display devices. Also there is a report that the tone reproduced LDR image on LDR display device is viewed better than HDR image on HDR display according to Oh [1] . For this reason, we propose a new method which can tonally reproduce HDR image into a natural LDR image as auto exposed (AE) one with minimum loss of image information.

Spectral printer modeling for transparency media: toward high dynamic range scene reproduction

Abstract: We propose a system for display of large format images such that natural scenes can be approximated in a laboratory setting, both spectrally and in dynamic range. The system uses a large area (48"x36") high intensity light box constructed using multiple xenon arc lamps with diffusers to maximize surface uniformity. This source is used as a back light for multiple transparency layers mounted on a rigid plexiglass substrate, where images are printed on the transparency layers using a wide format inkjet printer. A detailed transparency printer model for this system is described, where the spectral transmittance can be predicted with a high degree of accuracy for any given combination of input digital ink values (CMYKRGB). This spectral printer model, in conjunction with knowledge of the spectral characteristics of the back light, can be used to approximate the spectral radiance of a target scene. On a per-pixel level, nonlinear constrained optimization is used to solve for the combination of printer inks that produces the best estimate to the spectrum of the target scene. With this system, it is then possible to create realistic static images with a large dynamic range that can be used to benchmark camera systems in a controlled laboratory setting.

Exposure-adaptive color-image enhancement

Abstract: In many cases, it is not possible to faithfully capture shadow and highlight image data of a high dynamic range (HDR) scene using a common digital camera, due to its narrow dynamic range (DR). Conventional solutions tried to solve the problem with an captured image which has saturated highlight and/or lack of shadow information. In this situation, we introduce a color image enhancing method with the scene-adaptive exposure control. First, our method recommends an optimal exposure to obtain more information in highlight by the histogram-based scene analysis. Next, the proposed luminance and contrast enhancement is performed on the captured image. The main processing consists of luminance enhancement, multi-band contrast stretching, and color compensation. The luminance and chrominance components of input RGB data is separated by converting into HSV color space. The luminance is increased using an adaptive log function. Multi-band contrast stretching functions are applied to each sub-band to enhance shadow and highlight at the same time. To remove boundary discontinuities between sub-bands, the multi-level low-pass filtering is employed. The blurred image data represents local illumination while the contrast-stretched details correspond to reflectance of the scene. The restored luminance image is produced by the combination of multi-band contrast stretched image and multilevel low-pass filtered image. Color compensation proportional to the amount of luminance enhancement is applied to make an output image.

Enhancement tuning and control for high dynamic range images in multi-scale locally adaptive contrast enhancement algorithms

Abstract: For real-time imaging in surveillance applications, visibility of details is of primary importance to ensure customer confidence. If we display High Dynamic-Range (HDR) scenes whose contrast spans four or more orders of magnitude on a conventional monitor without additional processing, results are unacceptable. Compression of the dynamic range is therefore a compulsory part of any high-end video processing chain because standard monitors are inherently Low- Dynamic Range (LDR) devices with maximally two orders of display dynamic range. In real-time camera processing, many complex scenes are improved with local contrast enhancements, bringing details to the best possible visibility. In this paper, we show how a multi-scale high-frequency enhancement scheme, in which gain is a non-linear function of the detail energy, can be used for the dynamic range compression of HDR real-time video camera signals. We also show the connection of our enhancement scheme to the processing way of the Human Visual System (HVS). Our algorithm simultaneously controls perceived sharpness, ringing ("halo") artifacts (contrast) and noise, resulting in a good balance between visibility of details and non-disturbance of artifacts. The overall quality enhancement, suitable for both HDR and LDR scenes, is based on a careful selection of the filter types for the multi-band decomposition and a detailed analysis of the signal per frequency band.

Improved color reproduction based on CIELAB color space in integrated multi-scale retinex

Abstract: Recently, tone reproduction is widely used in the field of image enhancement and HDR imaging This method is especially used to provide the proper luminance so that captured images give the same sensation as the scene As a result, we can get high contrast and naturalness of colors There is ample literature on the topic of tone reproduction that has the objective of reproducing natural looking color in digital images In recent papers, IMSR (Integrated multi-scale Retinex) shows great naturalness in the result images Most methods, including IMSR, work in RGB or quasi-RGB color spaces, although some method adopted the use of luminance This raises hue distortion from the point of the human visual system, that is, hue distortion in CIELAB color space Accordingly, this paper proposes an enhanced IMSR method in a device-independent color space, CIELAB, to preserve hue and obtain high contrast and naturalness In order to achieve the devised objectives, a captured sRGB image is transformed to the CIELAB color space IMSR is then applied to only L* values, thus the balance of colors components are preserved This process causes unnatural saturation, therefore saturation adjustment is performed by applying the ratio of chroma variation at the sRGB gamut boundary according to the corrected luminance Finally, the adjusted CIELAB values are transformed to sRGB using the inverse transform function In the result images of the proposed method, containing both high and low luminance regions, visibility in dark shadow and bright regions was improved and color distortion was reduced

High Dynamic Range Imaging and LDR Expansion for Generating HDR Content

Abstract: In the last few years researches in the High Dynamic Range (HDR) Imaging field have focused on providing tools for expanding LDR content for the generation of HDR images and videos for HDR displays and Image Based Lighting. Furthermore, another important problem has been tackled, the space compression of HDR content using a tone mapping operator (TMOs) and its inverse. The goal of this report is to provide a comprehensive overview on HDR Imaging, and an in depth review on these emerging topics. Moreover, we are proposing how to classify and to validate them. Furthermore, limits of these methods are discussed, showing the remaining challenges for the future.

High-speed and high-dynamic range difference imaging based on the near-sensor image processing concept

Abstract: The paper describes the Near Sensor Image Processing (NSIP) paradigm developed in the early 1990s and shows that it was a precursor to recent architectures proposed for direct (in the sensor) image processing and high dynamic range (HDR) image sensing. Both of these architectures are based on the specific properties of CMOS light sensors, in particular the ability to continuously monitor the accumulation of photon-induced charge as a function of time. We further propose an extension of the original NSIP pixel to include a circuit that facilitates temporal and spatio-temporal processing.