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.

Tone mapping using color correction function and image decomposition in high dynamic range imaging

Abstract: In this paper, we propose a tone mapping (TM) method using color correction function (CCF) and image decomposition in high dynamic range (HDR) imaging. The CCF in the proposed TM is derived from the luminance compression function with the color constraint under which the color ratios, between the three color channels of the radiance map and dynamic range compression term, are preserved and color saturation is controlled. The proposed CCF is developed to locally perform the luminance compression and color saturation control in local TM. For image decomposition, we use a bilateral filter and apply the adaptive weight to the base layer of the luminance. Computer simulations with various sets of real, low dynamic range images show the effectiveness of the proposed TM algorithm in terms of the visual quality as well the local contrast. It can be used for contrast and color enhancement in various display and acquisition devices.

Spatially adaptive filtering for registration artifact removal in HDR video

Abstract: One method to extend the dynamic range of video captured with inexpensive cameras is to alternate the exposure time between frames and combine the information in adjacent frames using post-processing. This method requires no hardware modification, yet traditionally there is a quality tradeoff. Dynamic range expansion corresponds to an increased number of saturated pixels in individual frames, which along with occlusions contributes to registration artifacts. Therefore, we describe a “High Dynamic Range (HDR) Filter” that can mitigate these artifacts to produce a pleasing HDR video without exact frame registration. This filter builds upon the bilateral filter to smooth frames while maintaining important edges. Additionally, the filter strength locally adapts to corresponding motion vectors. Since regions with poor registration generally correspond to higher motion, smoothing here can reduce artifacts without degrading perceptual quality. Results show a significant improvement for HDR videos with fast local motion within saturated regions.

A model of local adaptation

Abstract: The visual system constantly adapts to different luminance levels when viewing natural scenes. The state of visual adaptation is the key parameter in many visual models. While the time-course of such adaptation is well understood, there is little known about the spatial pooling that drives the adaptation signal. In this work we propose a new empirical model of local adaptation, that predicts how the adaptation signal is integrated in the retina. The model is based on psychophysical measurements on a high dynamic range (HDR) display. We employ a novel approach to model discovery, in which the experimental stimuli are optimized to find the most predictive model. The model can be used to predict the steady state of adaptation, but also conservative estimates of the visibility (detection) thresholds in complex images. We demonstrate the utility of the model in several applications, such as perceptual error bounds for physically based rendering, determining the backlight resolution for HDR displays, measuring the maximum visible dynamic range in natural scenes, simulation of afterimages, and gaze-dependent tone mapping.

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.

High dynamic range analog-to-digital converter

Abstract: A high speed analog to digital converter ('ADC') (12) that can be used in a detector system (10). The ADC is coupled to a detector (14) and a processor (18). The detector (14) generates an analog signal in response to the detection of a trace sample, such as an ionized molecule or a beam of light. The processor (18) determines a baseline value and threshold value. Portions of the analog signal at or below the threshold are assigned the baseline value. The threshold typically corresponds to a value above the noise level in the system. The detector (14) thus removes undesirable noise from the readout value. The process can compensate for factors such as DC drift while providing accurate data regarding detection of the trace sample.