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.

Efficient HDR image acquisition using estimation of scenic dynamic range in camera images with different exposures

Abstract: Generally, to acquire an HDR image, many images that cover the entire dynamic range of the scene with different exposure times are required, then these images are fused into one HDR image. This paper proposes an efficient method for the HDR image acquisition with small number of images. First, we estimated scenic dynamic range using two images with different exposure times. These two images contain the upper and lower limit of the scenic dynamic range. Independently of the scene, according to varied exposure times, similar characteristics for both the maximum gray levels in images that include the upper limit and the minimum gray levels in images that include the lower limit are identified. After modeling these characteristics, the scenic dynamic range is estimated using the modeling results. This estimated scenic dynamic range is then used to select the proper exposure times for the acquisition of an HDR image. We selected only three proper exposure times because entire dynamic range of the cameras could be covered by three dynamic range of the cameras with different exposure times. To evaluate the error of the HDR image, experiments using virtual digital camera images were carried out. For several test images, the error of the HDR image using proposed method was comparable to that of the HDR image which utilize more than ten images for the HDR image acquisition.

Single exposure high dynamic range imaging with a conventional camera using cross-screen filters

Abstract: Real world scenes often contain both bright and dark regions, resulting in a high contrast ratio, beyond the capabilities of conventional cameras. For these cases, High Dynamic Range or HDR images can be captured with expensive hardware or by taking multiple exposures of the same scene. However, these methods cost extra resources — either spatial or temporal resolution is sacrificed, or more than one piece of hardware is needed. In this thesis, a novel technique is presented that is capable of capturing High Dynamic Range images in only one exposure of a conventional camera. We observe that most natural HDR images have only 2–5% pixels that are too bright compared to the rest of the scene to fall inside the dynamic range of a conventional camera. Our method spreads energy from these bright regions into the neighboring unsaturated pixels by defocus blurring. Bright pixels still get clipped in the captured image due to saturation of the sensor; but some information about these clipped pixels gets encoded or multiplexed in the form of superimposed glare patterns in the image. Frequency preservation and decoding of this information can be further improved by using a crossscreen filter instead of using defocus blur. Superimposed glare patterns are recovered with the help of natural image statistics. These glare patterns provide information about how much energy there is in the saturated pixels, which allows a tomography-like reconstruction of the saturated regions. Once the saturated regions are known, the rest of the image can be restored by removing the estimated glare patterns.

Savitzky–Golay Filtering-Based Fusion of Multiple Exposure Images for High Dynamic Range Imaging

Abstract: The problem of compositing multiple exposure images has attracted lots of researchers, over the past years. It all began with the problem of High Dynamic Range (HDR) imaging, for capturing scenes with vast differences in their dynamic range. Fine details in all the areas in these scenes cannot be captured with one single exposure setting of the camera aperture. This leads to multiple exposure images with each image containing accurate representation of different regions dimly lit, well lit and brightly lit in the scenes. One can make a combined HDR image out of these multiple exposure shots. This combination of multiple exposure shots leads to an image of a higher dynamic range in a different image format which cannot be represented in the traditional Low Dynamic Range (LDR) formats. Moreover HDR images cannot be displayed in traditional display devices suitable for LDR. So these images have to undergo a process called as tone mapping for further converting them to be suitable enough to be represented on usual LDR displays. An approach based on Savitzky–Golay parametric filtering which preserves edges, is proposed which uses filtered multiple exposure images to generate the alpha matte coefficients required for fusing the input multiple exposure set. The coefficients generated in the proposed approach helps in retaining the weak edges and the fine textures which are lost as a result of the under and over exposures. The proposed approach is similar in nature to the bilateral filter-based compositing approach for multiple exposure images in the literature but it is novel, in exploring the possibility of compositing using a parametric filtering approach. The proposed approach performs the fusion in the LDR domain and the fused output can also be displayed using standard LDR image formats on standard LDR displays. A brief comparison of the results generated by the proposed method and various other approaches, including the traditional exposure fusion, tone mapping-based techniques and bilateral filter-based approach is presented where in the proposed method compares well and fares better in majority of the test cases.

Theoretical study of an efficient bracketing camera system architecture

Abstract: Although High Dynamic Range (HDR) imaging has represented, in the recent years, the topic of important researches, it has not reached yet an excellent level of the HDR scenes ac quisition using the available co mponents. Indeed, many solu-tions have been proposed ranging from bracketing to the beamsp litter but none of these solutions is really consistent with the moving scenes representing light’s level difference. In this paper, we present an optical architecture, which exploits the stereoscopic cameras, ensuring the simultaneous capture of four different ex posures of the same image on four sensors with efficient use of the available light. We also present a short description of the implemented fusion algorithm implemented. Keywords : Stereoscopic cameras, beamsplitters, APEX , HDR Imaging, Cameras architecture, AMP 1. Introduction The extensive development of computer tools is in effervescen ce year by year. It remains on e of the emerging techniques introduced in numerous applications such as quality control, medicine, and video surveillance. The artificial vision tech-niques are adapted to the envisaged applica tions and to the associated constraints. Along with this, the researches in the field of HDR images’ are constantly evolving. Indeed, the process of capturing HDR images has been the work subject of many researchers and hundreds of artists and photographers. As a result, there are many articles and patents describing methods and systems for capturing HDR images. The easiest way to HDR imag-ing involves taking a series of pictures with different exposure times [1, 2]. A lthough this method works well for static scenes, it is unfortunately not well suited for video because of different exposure times for each image, which result in varying amounts of motion blur and other effects occurring after the time of use. However, researchers have extended this approach to video capturing with alternating bright and dark exhibitions [3, 4]. In our case, we will use the stereoscopic technology to generate High Dynamic Range (HDR) images. In order to achieve that, we require three to five images with different exposures. With the combination between two lenses of a camera and a beam splitter, we can get up to four differen t images. Thus, we will study the necessary diaphragm opening allowing us to get the best exposures and define the architecture that we would deploy. The paper will be organized as follow. In the section II, we will discuss about the researches related to stereoscopic cameras and HDR images. Then, Section III will detail the proposed architectur e, the criteria to be met and the results that are expected to get. Finally, th is article will finish by a conclusion and an introduction of some perspectives.

High-Dynamic-Range Imaging Using Nanowires

Abstract: High-dynamic-range (HDR) imaging applications are increasing rapidly due to their advantages to increase the color quality of the pictures that can be accessed now even from the cellphones. Combining HDR with multispectral images could give us the opportunity to not only have great color information but also to analyze different compositions of materials. However, the use of these techniques is still limited due to portability and costs. In this work, we present linear and nonlinear methods to generate HDR images using a novel single capture multispectral camera based on nanowires sensors. The results presented here show an error reduction in color estimation compared to previous methods.