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.

A 113 dB SNR oversampling DAC with segmented noise-shaped scrambling

Abstract: Consumer formats such as DVD push the performance of audio D/A converters to higher and higher levels. D/A converters with high dynamic range and low cost are now in demand. Previous /spl Sigma//spl Delta/ D/A converters have used 1b digital modulators with switched-capacitor analog filters. The noise of switched-capacitor filters is limited by thermal KT/C noise, so achieving high-dynamic range requires an impractical amount of on-chip capacitance. The design shown differs in several ways from previous /spl Sigma//spl Delta/ D/A converters. A continuous-time output stage avoids the thermal noise added by reasonable-size switched-capacitor circuits. Continuous-time /spl Sigma//spl Delta/ circuits have several serious problems, including high sensitivity to clock jitter, difficulty in filtering the output waveform, and extreme sensitivity to intersymbol interference in the pulse output waveform. These problems are reduced.

Ultimate SLAM? Combining Events, Images, and IMU for Robust Visual SLAM in HDR and High-Speed Scenarios

Abstract: Event cameras are bioinspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide reliable visual information during high-speed motions or in scenes characterized by high dynamic range. However, event cameras output only little information when the amount of motion is limited, such as in the case of almost still motion. Conversely, standard cameras provide instant and rich information about the environment most of the time (in low-speed and good lighting scenarios), but they fail severely in case of fast motions, or difficult lighting such as high dynamic range or low light scenes. In this letter, we present the first state estimation pipeline that leverages the complementary advantages of these two sensors by fusing in a tightly coupled manner events, standard frames, and inertial measurements. We show on the publicly available Event Camera Dataset that our hybrid pipeline leads to an accuracy improvement of 130% over event-only pipelines, and 85% over standard-frames-only visual-inertial systems, while still being computationally tractable. Furthermore, we use our pipeline to demonstrate-to the best of our knowledge-the first autonomous quadrotor flight using an event camera for state estimation, unlocking flight scenarios that were not reachable with traditional visual-inertial odometry, such as low-light environments and high dynamic range scenes. Videos of the experiments: http://rpg.ifi.uzh.ch/ultimateslam.html.

Optimizing a Tone Curve for Backward-Compatible High Dynamic Range Image and Video Compression

Abstract: For backward compatible high dynamic range (HDR) video compression, the HDR sequence is reconstructed by inverse tone-mapping a compressed low dynamic range (LDR) version of the original HDR content. In this paper, we show that the appropriate choice of a tone-mapping operator (TMO) can significantly improve the reconstructed HDR quality. We develop a statistical model that approximates the distortion resulting from the combined processes of tone-mapping and compression. Using this model, we formulate a numerical optimization problem to find the tone-curve that minimizes the expected mean square error (MSE) in the reconstructed HDR sequence. We also develop a simplified model that reduces the computational complexity of the optimization problem to a closed-form solution. Performance evaluations show that the proposed methods provide superior performance in terms of HDR MSE and SSIM compared to existing tone-mapping schemes. It is also shown that the LDR image quality resulting from the proposed methods matches that produced by perceptually-based TMOs.

Coherence Pattern-Guided Compressive Sensing with Unresolved Grids

Abstract: Highly coherent sensing matrices arise in discretization of continuum imaging problems such as radar and medical imaging when the grid spacing is below the Rayleigh threshold. Algorithms based on techniques of band exclusion (BE) and local optimization (LO) are proposed to deal with such coherent sensing matrices. These techniques are embedded in the existing compressed sensing algorithms, such as Orthogonal Matching Pursuit (OMP), Subspace Pursuit (SP), Iterative Hard Thresholding (IHT), Basis Pursuit (BP), and Lasso, and result in the modified algorithms BLOOMP, BLOSP, BLOIHT, BP-BLOT, and Lasso-BLOT, respectively. Under appropriate conditions, it is proved that BLOOMP can reconstruct sparse, widely separated objects up to one Rayleigh length in the Bottleneck distance independent of the grid spacing. One of the most distinguishing attributes of BLOOMP is its capability of dealing with large dynamic ranges. The BLO-based algorithms are systematically tested with respect to four performance metrics: dynamic range, noise stability, sparsity, and resolution. With respect to dynamic range and noise stability, BLOOMP is the best performer. With respect to sparsity, BLOOMP is the best performer for high dynamic range, while for dynamic range near unity BP-BLOT and Lasso-BLOT with the optimized regularization parameter have the best performance. In the noiseless case, BP-BLOT has the highest resolving power up to certain dynamic range. The algorithms BLOSP and BLOIHT are good alternatives to BLOOMP and BP/Lasso-BLOT: they are faster than both BLOOMP and BP/Lasso-BLOT and share, to a lesser degree, BLOOMP's amazing attribute with respect to dynamic range. Detailed comparisons with the algorithms Spectral Iterative Hard Thresholding (SIHT) and the frame-adapted BP demonstrate the superiority of the BLO-based algorithms for the problem of sparse approximation in terms of highly coherent, redundant dictionaries.

Extending Quality Metrics to Full Luminance Range Images

Abstract: Many quality metrics take as input gamma corrected images and assume that pixel code values are scaled perceptually uniform. Although this is a valid assumption for darker displays operating in the luminance range typical for CRT displays (from 0.1 to 80 cd/m2), it is no longer true for much brighter LCD displays (typically up to 500 cd/m2), plasma displays (small regions up to 1000 cd/m2) and HDR displays (up to 3000 cd/m2). The distortions that are barely visible on dark displays become clearly noticeable when shown on much brighter displays. To estimate quality of images shown on bright displays, we propose a straightforward extension to the popular quality metrics, such as PSNR and SSIM, that makes them capable of handling all luminance levels visible to the human eye without altering their results for typical CRT display luminance levels. Such extended quality metrics can be used to estimate quality of high dynamic range (HDR) images as well as account for display brightness.