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.

Modelling of high dynamic range logarithmic CMOS image sensors

Abstract: The quality of the output images from high dynamic range logarithmic sensors is limited by fixed pattern noise (FPN) which is caused by device mismatches within pixels in an array. It leads to inferior image quality in comparison to image from other sensors of similar resolution. Previous design and post-chip attempts to correct this type of noise have been either impractical or resulted in other complexities. However, FPN correction can be attempted using an accurate model approach for the response of this type of pixel. A three parameter model, previously suggested for logarithmic pixels, has been tried for this purpose. In this paper a simple parameter extraction procedure is proposed using this model to calibrate and correct FPN. The result is a model that works well over six decades of illumination but fails at high photocurrents. It is shown that this is caused by a breakdown in an assumption used to create the three parameter models. Consequently, a new four parameter model is developed that fits the data over six decades, and is usable in FPN correction for many wide current range applications that require complete and accurate characterisation.

High dynamic range image sensor architectures

Abstract: Digital photographers continuously demand more performance from their equipment. Digital camera performance is defined by a set of parameters including dynamic range, noise, frame rate, resolution, and color. Amongst these parameters dynamic range is becoming increasingly more important. This is true because the human eye typically has a wider dynamic range than a digital camera. In this paper we define dynamic range as the ratio of the maximum to the minimum signal that can be detected. At the heart of all digital cameras is either a CCD or a CMOS image sensor (CIS). The dynamic range of the sensor typically limits the dynamic range of the camera. In this paper we review five CIS architectures that are designed to improved dynamic range. We start by reviewing standard CCD and CIS architectures and then present a simple sensor model. Using this model we show how signal to noise ratio (SNR) can be used to evaluate different wide dynamic range (WDR) sensor architectures. Then we sequentially review five different wide dynamic range techniques. The first WDR technique is multiple gains, and the second technique is non-linear pixel response. The third technique is variable exposure, and the forth technique is well capacity recycling. The fifth and final technique is time to saturation. For each of these techniques we present the pixel level circuitry and its advantages and disadvantages. Furthermore, all of these techniques are compared based on SNR and implementation complex. We discuss how implementation complexity affects signal processing in a digital camera, and other parameters in the sensor such as quantum efficiency and read noise. We conclude with a few summary comments.

Robust High Dynamic Range (HDR) Imaging with Complex Motion and Parallax

Abstract: High dynamic range (HDR) imaging is widely used in consumer photography, computer game rendering, autonomous driving, and surveillance systems. Reconstructing ghosting-free HDR images of dynamic scenes from a set of multi-exposure images is a challenging task, especially with large object motion, disparity, and occlusions, leading to visible artifacts using existing methods. In this paper, we propose a Pyramidal Alignment and Masked merging network (PAMnet) that learns to synthesize HDR images from input low dynamic range (LDR) images in an end-to-end manner. Instead of aligning under/overexposed images to the reference view directly in pixel-domain, we apply deformable convolutions across multiscale features for pyramidal alignment. Aligned features offer more flexibility to refine the inevitable misalignment for subsequent merging network without reconstructing the aligned image explicitly. To make full use of aligned features, we use dilated dense residual blocks with squeeze-and-excitation (SE) attention. Such attention mechanism effectively helps to remove redundant information and suppress misaligned features. Additional mask-based weighting is further employed to refine the HDR reconstruction, which offers better image quality and sharp local details. Experiments demonstrate that PAMnet can produce ghosting-free HDR results in the presence of large disparity and motion. We present extensive comparative studies using several popular datasets to demonstrate superior quality compared to the state-of-the-art algorithms.

Characterization and Simple Fixed Pattern Noise Correction in Wide Dynamic Range “Logarithmic” Imagers

Abstract: Wide dynamic range logarithmic imagers can render naturally illuminated scenes while preserving detail and contrast information at a lower cost than high dynamic range linear sensors. However, the quality of the output is severely degraded by fixed pattern noise (FPN). Although previous FPN correction techniques can eliminate the dominant additive form of this noise, the contrast threshold of the imager over a wide illumination range is poor compared to the human visual system. In this paper, it is shown that a four-parameter model fits the measured characteristic response of wide dynamic range pixels over 11 decades of input current. A comparison of the responses of 200 pixels shows that there are significant variations in all four parameters. A procedure is described that allows the four pixel parameters to be obtained from the response of each pixel to five input currents. However, a much simpler procedure is shown to correct FPN, leading to a contrast threshold comparable to the human visual system over the five decades required to image wide-dynamic-range, naturally illuminated scenes.

A large field CCD system for quantitative imaging of microarrays.

Abstract: We describe a charge-coupled device (CCD) imaging system for microarrays capable of acquiring quantitative, high dynamic range images of very large fields. Illumination is supplied by an arc lamp, and filters are used to define excitation and emission bands. The system is linear down to fluorochrome densities 1000. Resolution referred to the sample is 10 microm, sufficient for obtaining quantitative multicolor images from >30,000 array elements in an 18 mm x 18 mm square.