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.

Method and apparatus for encoding high dynamic range video

Abstract: A method and apparatus for encoding high dynamic range video by means of video compression is shown. The method comprises the steps of providing high dynamic range (HDR) tristimulus color data (XYZ) for each frame of the video and threshold versus intensity data for a human observer; constructing a perceptually conservative luminance transformation from continuous luminance data (Y) to discrete values (Lp) using said threshold versus intensity data for the human observer; transforming the HDR tristimulus color data into perceptually linear color data of three color channels (Lp, u′, v′) for obtaining visually lossless compressed frames; estimating motion vector of said consecutive frames of the video and compensating the difference of the tristimulus color data for performing an inter-frame encoding and an inter-frame compression; transforming the compensated differences of the tristimulus color data to frequency space data; quantizing said frequency space data; variable-length encoding of the quantized frequency space data and storing or transmitting a stream of visual data resulting from the encoded quantized frequency space data.

Vehicle vision system with high dynamic range

Abstract: A vehicular vision system is disclosed (Fig. 1) comprising a high dynamic range (101, 102). The systems and methods are advantages for rear vision, collision avoidance, obstacle detection, adaptive cruise control, rain sensing (100), exterior light control (110), and lane departure warning, as well as other applications where a given scene may comprise objects having widely varying brightness values (120).

Structured light field 3D imaging.

Abstract: In this paper, we propose a method by means of light field imaging under structured illumination to deal with high dynamic range 3D imaging. Fringe patterns are projected onto a scene and modulated by the scene depth then a structured light field is detected using light field recording devices. The structured light field contains information about ray direction and phase-encoded depth, via which the scene depth can be estimated from different directions. The multidirectional depth estimation can achieve high dynamic 3D imaging effectively. We analyzed and derived the phase-depth mapping in the structured light field and then proposed a flexible ray-based calibration approach to determine the independent mapping coefficients for each ray. Experimental results demonstrated the validity of the proposed method to perform high-quality 3D imaging for highly and lowly reflective surfaces.

Modeling, calibration, and correction of nonlinear illumination-dependent fixed pattern noise in logarithmic CMOS image sensors

Abstract: At present, most CMOS image sensors use an array of pixels with a linear response. However, pixels with a logarithmic response are also possible and are capable of imaging high dynamic range scenes without saturating. Unfortunately, logarithmic image sensors suffer from fixed pattern noise (FPN). Work reported in the literature generally assumes the FPN is independent of illumination. This paper develops a nonlinear model y=a+bln(c+x)+/spl epsi/ of a pixel for the digital response y to an illuminance x and shows that the FPN arises from a variation of the offset a, gain b, and bias c from pixel to pixel. Equations are derived to estimate these parameters by calibrating images of uniform stimuli, taken with varying illuminances. Experiments with a Fuga 15d image sensor, demonstrating parameter calibration and FPN correction, show that the nonlinear model outperforms previous models that assume either only offset or offset and gain variation.

High dynamic range scanning technique

Abstract: Measuring objects with high surface reflectivity variations (i.e., high dynamic range) is challenging for any optical method. This paper addresses a high dynamic range scanning (HDRS) technique that can measure this type of objects. It takes advantage of one merit of a phase-shifting algorithm: pixel-by-pixel phase retrieval. For each measurement, multiple shots of fringe images with different exposures are taken. And a sequence of fringe images with different overall brightness are captured: the brightest fringe images have good fringe quality for darker areas although the brighter areas may be saturated; while the darkest fringe images have good fringe quality in brighter areas although the fringes in the darker areas may be invisible. The sequence of fringe images is 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 the unsaturated corresponding pixel from one shot. 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 properties.