High dynamic range

About: High dynamic range is a research topic. Over the lifetime, 4280 publications have been published within this topic receiving 76293 citations. The topic is also known as: HDR.

Multi-sensor camera system

Abstract: High dynamic range images are generated using conventional dynamic range cameras. A first camera is configured with exposure settings that are optimized for brighter regions, while a second camera assembly is optimized for darker regions. The cameras can be rectified and can capture concurrently such that objects are relatively aligned, with global and local misregistrations being minimized. The image data is analyzed to determine regions where the image data from one camera or the other provides higher quality, such as where the brightness values fall between a noise floor and a saturation level. If image data from both sets have values within that range then the values can be combined, such as with a weighted average. A composite image is generated that includes more uniform color and brightness than in either image individually, or that could have been captured using a single camera of similar cost and capabilities.

Multiple A to D converters for enhanced dynamic range

Abstract: Systems and methods for providing analog to digital conversion with improved dynamic range. Multiple low cost analog to digital converters may be used in parallel to provide the dynamic range of a single high resolution analog to digital converter that would otherwise be available only at very high cost. One application is an orthogonal frequency division multiplexing (OFDM) digital receiver which requires high dynamic range analog to digital conversion for accurate reception.

Digital-pixel Focal Plane Array Development

Abstract: Since 2006, MIT Lincoln Laboratory has been developing Digital-pixel Focal Plane Array (DFPA) readout integrated circuits (ROICs) To date, four 256 × 256 30 μm pitch DFPA designs with in-pixel analog to digital conversion have been fabricated using IBM 90 nm CMOS processes The DFPA ROICs are compatible with a wide range of detector materials and cutoff wavelengths; HgCdTe, QWIP, and InGaAs photo-detectors with cutoff wavelengths ranging from 16 to 145 μm have been hybridized to the same digital-pixel readout The digital-pixel readout architecture offers high dynamic range, A/C or D/C coupled integration, and on-chip image processing with low power orthogonal transfer operations The newest ROIC designs support two-color operation with a single Indium bump connection Development and characterization of the two-color DFPA designs is presented along with applications for this new digital readout technology

Robust artifact-free high dynamic range imaging of dynamic scenes

Abstract: The irradiance range of the real-world scene is often beyond the capability of digital cameras. Therefore, High Dynamic Range (HDR) images can be generated by fusing images with different exposure of the same scene. However, moving objects pose the most severe problem in the HDR imaging, leading to the annoying ghost artifacts in the fused image. In this paper, we present a novel HDR technique to address the moving objects problem. Since the input low dynamic range (LDR) images captured by a camera act as static linear related backgrounds with moving objects during each individual exposures, we formulate the detection of foreground moving objects as a rank minimization problem. Meanwhile, in order to eliminate the image blurring caused by background slightly change of LDR images, we further rectify the background by employing the irradiances alignment. Experiments on image sequences show that the proposed algorithm performs significant gains in synthesized HDR image quality compare to state-of-the-art methods.

Nighttime Visibility Enhancement by Increasing the Dynamic Range and Suppression of Light Effects

Abstract: Most existing nighttime visibility enhancement methods focus on low light. Night images, however, do not only suffer from low light, but also from man-made light effects such as glow, glare, floodlight, etc. Hence, when the existing nighttime visibility enhancement methods are applied to these images, they intensify the effects, degrading the visibility even further. High dynamic range (HDR) imaging methods can address the low light and over-exposed regions, however they cannot remove the light effects, and thus cannot enhance the visibility in the affected regions. In this paper, given a single nighttime image as input, our goal is to enhance its visibility by increasing the dynamic range of the intensity, and thus can boost the intensity of the low light regions, and at the same time, suppress the light effects (glow, glare) simultaneously. First, we use a network to estimate the camera response function (CRF) from the input image to linearise the image. Second, we decompose the linearised image into low-frequency (LF) and high-frequency (HF) feature maps that are processed separately through two networks for light effects suppression and noise removal respectively. Third, we use a network to increase the dynamic range of the processed LF feature maps, which are then combined with the processed HF feature maps to generate the final output that has increased dynamic range and suppressed light effects. Our experiments show the effectiveness of our method in comparison with the state-of-the-art nighttime visibility enhancement methods.