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.

Perception-based high dynamic range compression in gradient domain

Abstract: It is often required to map the radiances of a real scene to a smaller dynamic range so that the image can be properly displayed. However, most such algorithms suffer from the halo artifact or require manual parameter tweaking that is often a tedious process for the user. We propose an automatic algorithm for high dynamic range compression based on the properties of human visual system. The algorithm is performed in the gradient domain to avoid the halo artifact. It automates the parameter adjustment process while preserving the image details. Performance comparison is provided to illustrate the advantages of the proposed algorithm.

Enhancement of contrast and resolution of B-mode plane wave imaging (PWI) with non-linear filtered delay multiply and sum (FDMAS) beamforming

Abstract: FDMAS has been successfully used in microwave imaging for breast cancer detection. FDMAS gained its popularity due to its capability to produce results faster than any other adaptive beamforming technique such as minimum variance (MV) which requires higher computational complexity. The average computational time for single point spread function (PSF) at 40 mm depth for FDMAS is 87 times faster than MV. The new beamforming technique has been tested on PSF and cyst phantoms experimentally with the ultrasound array research platform version 2 (UARP II) using a 3–8 MHz 128 element clinical transducer. FDMAS is able to improve both imaging contrast and spatial resolution as compared to DAS. The wire phantom main lobes lateral resolution improved in FDMAS by 40.4% with square pulse excitation signal when compared to DAS. Meanwhile the contrast ratio (CR) obtained for an anechoic cyst located at 15 mm depth for PWI with DAS and FDMAS are −6.2 dB and −14.9 dB respectively. The ability to reduce noise from off axis with auto-correlation operation in FDMAS pave the way to display the B-mode image with high dynamic range. However, the contrast to noise ratio (CNR) measured at same cyst location for FDMAS give less reading compared to DAS. Nevertheless, this drawback can be compensated by applying compound plane wave imaging (CPWI) technique on FDMAS. In overall the new FDMAS beamforming technique outperforms DAS in laboratory experiments by narrowing its main lobes and increases the image contrast without sacrificing its frame rates.

Superconducting bandpass delta-sigma modulator

Abstract: Bandpass delta-sigma modulators digitize narrowband signals with high dynamic range and linearity. The required sampling rate is only a few times higher than the centre frequency of the input. This paper presents a superconducting bandpass delta-sigma modulator for direct analogue-to-digital conversion of RF signals in the GHz range. The input signal is capacitively coupled to one end of a microstrip transmission line, and a single flux quantum balanced comparator quantizes the current flowing out of the other end. Quantization noise is suppressed at the quarter-wave resonance of the transmission line (about 2 GHz in our design). Circuit performance at a 20 GHz sampling rate has been studied with several long JSIM simulations. Full-scale (FS) input sensitivity is 20 mV (rms), and in-band noise is -53 dBFS and -57 dBFS over bandwidths of 39 MHz and 19.5 MHz, respectively. In-band intermodulation distortion is better than -69 dBFS.

Importance of the Dynamic Range of an Analysis Windowfunction for Phase-Only and Magnitude-Only Reconstruction of Speech

Abstract: The short-time Fourier transform (STFT) of a speech signal has two components: the short-time magnitude spectrum and the short-time phase spectrum. It is traditionally believed that the short-time magnitude spectrum plays the dominant role for speech perception at small window durations (20-40 ms). However, recent perceptual studies have shown that the short-time phase spectrum can contribute as much to speech intelligibility as the short-time magnitude spectrum. It was observed that the use of the rectangular (non-tapered) analysis window for the computation of the short-time phase spectrum is more advantageous than the use of the Hamming (tapered) analysis window. This paper investigates the effect that the dynamic range of an analysis window has on the intelligibility of speech for phase-only and magnitude-only stimuli. For this purpose, the Chebyshev analysis window with adjustable equi-ripple side-lobes is employed. Two types of magnitude-only stimuli are investigated: random phase and zero phase. It is shown that the intelligibility of the magnitude-only stimuli constructed with zero phase is independent of the dynamic range of the analysis window, while the random phase stimuli are intelligible only for analysis windows with high dynamic range. This study also shows that for low dynamic range analysis windows, the short-time phase spectrum at small window durations (20-40 ms) contributes as much as to speech intelligibility as the short-time magnitude spectrum.

CMOS Monolithic Active Pixel Sensors (MAPS): Developments and future outlook

Abstract: Re-invented in the early 1990s, on both sides of the Atlantic, Monolithic Active Pixel Sensors (MAPS) in a CMOS technology are today the most sold solid-state imaging devices, overtaking the traditional technology of Charge-Coupled Devices (CCD). The slow uptake of CMOS MAPS started with low-end applications, for example web-cams, and is slowly pervading the high-end applications, for example in prosumer digital cameras. Higher specifications are required for scientific applications: very low noise, high speed, high dynamic range, large format and radiation hardness are some of these requirements. This paper will present a brief overview of the CMOS Image Sensor technology and of the requirements for scientific applications. As an example, a sensor for X-ray imaging will be presented. This sensor was developed within a European FP6 Consortium, intelligent imaging sensors (I-ImaS).