High-dynamic-range imaging

About: High-dynamic-range imaging is a research topic. Over the lifetime, 766 publications have been published within this topic receiving 22577 citations.

An Automatic Weight-Based High Dynamic Range Imaging Syntheses with Multiple Different Exposed Low Dynamic Range Images

Abstract: High dynamic range (HDR) imaging offers the capture of faithful representations of real world scenes to become a powerful technique in many areas, providing the maximum amount of detail data for radiologists to examine medical MR images. Now, HDR imaging is widely utilized in surveillance, remote sensing, and space research. This paper proposes a simple and effective scheme to generate a single HDR image combined by multiple low dynamic range (LDR) images of a scene with different exposures. The proposed algorithm first divides each LDR image into non-overlapping blocks of the same size, and then evaluate each block‟s average intensity and the statistical values of intensities of the whole LDR images. The proposed approach gives weight for each block according to each block‟s average intensity. The final output block is assigned as a weighted average of the input blocks acquired at different exposures. The experimental results show that the proposed approach has three major advantages: (i) the proposed algorithm is simple and effective, (ii) the proposed algorithm is time saving, due to operating completely on intensity only, (iii) there are no restrictions in the image dynamic color ranges in the proposed algorithm.

Forward and backward tone mapping of High Dynamic Range images based on subband architecture

Abstract: This paper presents a novel High Dynamic Range (HDR) tone mapping (TM) system based on sub-band architecture. Standard wavelet filters of Daubechies, Symlets, Coiflets and Biorthogonal were used to estimate the proposed system performance in terms of Low Dynamic Range (LDR) image quality and reconstructed HDR image fidelity. During TM stage, the HDR image is firstly decomposed in sub-bands using symmetrical analysis-synthesis filter bank. The transform coefficients are then rescaled using a predefined gain map. The inverse Tone Mapping (iTM) stage is straightforward. Indeed, the LDR image passes through the same sub-band architecture. But, instead of reducing the dynamic range, the LDR content is boosted to an HDR representation. Moreover, in our TM sheme, we included an optimization module to select the gain map components that minimize the reconstruction error, and consequently resulting in high fidelity HDR content. Comparisons with recent state-of-the-art methods have shown that our method provides better results in terms of visual quality and HDR reconstruction fidelity using objective and subjective evaluations.

High dynamic range imaging

Abstract: A method for high dynamic range imaging using more than two capture intervals, where images are captured in a repeating sequence that avoids interlace bounce, and overlapping groups of combined images form composite frames for output, and an imaging system comprising an imaging array, processing means and a display, wherein the imaging array is operable to capture a succession of images by detecting incident light and the processing means is operable to process said images as required, and pass the processed images to the display for output.

Exploiting redundancy in color-polarization filter array images for dynamic range enhancement.

Abstract: Color-polarization filter array (CPFA) sensors are able to capture linear polarization and color information in a single shot. For a scene that contains a high dynamic range of irradiance and polarization signatures, some pixel values approach the saturation and noise levels of the sensor. The most common CPFA configuration is overdetermined, and contains four different linear polarization analyzers. Assuming that not all pixel responses are equally reliable in CPFA channels, one can therefore apply the high dynamic range imaging scheme to improve the Stokes estimation from a single CPFA image. Here I present this alternative methodology and show qualitative and quantitative results on real data.

Luminance maps from High Dynamic Range imaging: photometric, radiometric and geometric calibrations

Abstract: Luminance maps created on the basis of High Dynamic Range Imaging is a technique increasingly used to study the visual environment. But creating HDR images with commercially affordable equipment requires a tedious calibration process, during which several steps could go wrong without anyone noticing it. This paper aims to provide an overview of the HDR calibration process, including different options, attention points and common mistakes. For inaccuracies and errors to be more easily detected and corrected, it is essential to understand each transformation applied to the images. Therefore, the capture of multiple exposure photographs, the response curve derivation, the HDR image generation, the vignetting and neutral density filter correction, the absolute calibration, and the geometrical reprojection stages are addressed. A more detailed description of the geometrical reprojection, especially required when working on glare assessment, is given as this topic has not yet been dealt with in the literature.