High-dynamic-range imaging

About: High-dynamic-range imaging is a research topic. Over the lifetime, 766 publications have been published within this topic receiving 22577 citations.

In-pixel high dynamic range imaging system and imaging sensor pixels

Abstract: The application relates to an in-pixel high dynamic range imaging system and imaging sensor pixels. Embodiments of the invention describe providing high dynamic range imaging (HDRI or simply HDR) to an imaging pixel by coupling a floating diffusion node of the imaging pixel to a plurality of metal-oxide semiconductor (MOS) capacitance regions. It is understood that a MOS capacitance region only turns on (i.e., changes the overall capacitance of the floating diffusion node) when the voltage at the floating diffusion node (or a voltage difference between a gate node and the floating diffusion node) is greater than its threshold voltage; before the MOS capacitance region is on it does not contribute to the overall capacitance or conversion gain of the floating diffusion node. Each of the MOS capacitance regions will have different threshold voltages, thereby turning on at different illumination conditions. This increases the dynamic range of the imaging pixel, thereby providing HDR for the host imaging system.

Compression efficiency of HDR/LDR content

Abstract: High Dynamic Range (HDR) imaging is capable of delivering a wider range of luminance and color gamut compared to Standard Dynamic Range (SDR), offering to viewers a visual quality of experience close to that of real-life. In this study, we evaluate the quality of coded original HDR streams and HDR streams reconstructed from SDR videos and metadata, both compressed by the HEVC standard. Our evaluations have shown that the single HDR approach is largely preferred over the SDR counterpart.

Method for high dynamic range imaging

Abstract: A method for high dynamic range imaging includes the steps of: (a) arranging at least two parallel cameras and meanwhile capturing a plurality of images of one scene with different exposures by at least the two cameras; (b) adjusting the captured images for the same exposure thereof subject to the response functions of the cameras respectively and then defining a plurality of characteristic spots in each of the images; (c) combining the characteristic spots corresponding to the images respectively to get a displacement of the corresponding characteristic spot in each image and to further get a disparity map; and (d) applying the displacement between the two corresponding characteristic spots in the corresponding images and synthesizing the images to form a synthetic image, by which a plurality of cameras can capture images with different exposures at the same time spot to synthesize a high dynamic range image and derive the disparity map

High dynamic range imaging with a single-mode pupil remapping system : a self-calibration algorithm for redundant interferometric arrays

Abstract: The correction of the influence of phase corrugation in the pupil plane is a fundamental issue in achieving high dynamic range imaging. In this paper, we investigate an instrumental setup which consists in applying interferometric techniques on a single telescope, by filtering and dividing the pupil with an array of single-mode fibers. We developed a new algorithm, which makes use of the fact that we have a redundant interferometric array, to completely disentangle the astronomical object from the atmospheric perturbations (phase and scintillation). This self-calibrating algorithm can also be applied to any - diluted or not - redundant interferometric setup. On an 8 meter telescope observing at a wavelength of 630 nm, our simulations show that a single mode pupil remapping system could achieve, at a few resolution elements from the central star, a raw dynamic range up to 10^6; depending on the brightness of the source. The self calibration algorithm proved to be very efficient, allowing image reconstruction of faint sources (mag = 15) even though the signal-to-noise ratio of individual spatial frequencies are of the order of 0.1. We finally note that the instrument could be more sensitive by combining this setup with an adaptive optics system. The dynamic range would however be limited by the noise of the small, high frequency, displacements of the deformable mirror.

High dynamic range imaging pipeline on the GPU

Abstract: Use of high dynamic range (HDR) images and video in image processing and computer graphics applications is rapidly gaining popularity. However, creating and displaying high resolution HDR content on CPUs is a time consuming task. Although some previous work focused on real-time tone mapping, implementation of a full HDR imaging (HDRI) pipeline on the GPU has not been detailed. In this article we aim to fill this gap by providing a detailed description of how the HDRI pipeline, from HDR image assembly to tone mapping, can be implemented exclusively on the GPU. We also explain the trade-offs that need to be made for improving efficiency and show timing comparisons for CPU versus GPU implementations of the HDRI pipeline.