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.

Joint focus stacking and high dynamic range imaging

Abstract: Focus stacking and high dynamic range (HDR) imaging are two paradigms of computational photography. Focus stacking aims to produce an image with greater depth of field (DOF) from a set of images taken with different focus distances, whereas HDR imaging aims to produce an image with higher dynamic range from a set of images taken with different exposure settings. In this paper, we present an algorithm which combines focus stacking and HDR imaging in order to produce an image with both higher dynamic range and greater DOF than any of the input images. The proposed algorithm includes two main parts: (i) joint photometric and geometric registration and (ii) joint focus stacking and HDR image creation. In the first part, images are first photometrically registered using an algorithm that is insensitive to small geometric variations, and then geometrically registered using an optical flow algorithm. In the second part, images are merged through weighted averaging, where the weights depend on both local sharpness and exposure information. We provide experimental results with real data to illustrate the algorithm. The algorithm is also implemented on a smartphone with Android operating system.

Halo-Free Multi-Exposure Image Fusion Based on Sparse Representation of Gradient Features

Abstract: Due to sharp changes in local brightness in high dynamic range scenes, fused images obtained by the traditional multi-exposure fusion methods usually have an unnatural appearance resulting from halo artifacts. In this paper, we propose a halo-free multi-exposure fusion method based on sparse representation of gradient features for high dynamic range imaging. First, we analyze the cause of halo artifacts. Since the range of local brightness changes in high dynamic scenes may be far wider than the dynamic range of an ordinary camera, there are some invalid, large-amplitude gradients in the multi-exposure source images, so halo artifacts are produced in the fused image. Subsequently, by analyzing the significance of the local sparse coefficient in a luminance gradient map, we construct a local gradient sparse descriptor to extract local details of source images. Then, as an activity level measurement in the fusion method, the local gradient sparse descriptor is used to extract image features and remove halo artifacts when the source images have sharp local changes in brightness. Experimental results show that the proposed method obtains state-of-the-art performance in subjective and objective evaluation, particularly in terms of effectively eliminating halo artifacts.

Image data aggregating high dynamic range imaging systems and associated methods

Abstract: An image data aggregating high dynamic range imaging system includes an image sensor for generating N image data sets from an array of photodiodes, where N is an integer greater than one. The image sensor is adapted to generate each of the N image data sets with a different respective exposure time duration of the array of photodiodes. The system further includes an image data aggregating module for aggregating the N image data sets to obtain a virtual long exposure image data set.

Alternating line high dynamic range imaging

Abstract: In this paper, a novel method of improving dynamic range of imaging device is proposed. Unlike multi-capture HDR methods, the suggested method requires only a small modification to existing CMOS imaging sensor. By changing exposure time line by line, one can obtain a multi-exposure image in a single capture of an image. With such captured image, digital image processing algorithms are applied to recover the lost vertical resolution with minimal degradation. This paper will cover overall system issues as well as detailed description of the algorithms applied to recover high dynamic range image.