Tone mapping for high dynamic range images

Tone mapping is an essential step for the reproduction of "nice looking" images. It provides the mapping between the luminances of the original scene to the output device's display values. When the dynamic range of the captured scene is smaller or larger than that of the display device, tone mapping expands or compresses the luminance ratios. We address the problem of tone mapping high dynamic range (HDR) images to standard displays (CRT, LCD) and to HDR displays. With standard displays, the dynamic range of the captured HDR scene must be compressed significantly, which can induce a loss of contrast resulting in a loss of detail visibility. Local tone mapping operators can be used in addition to the global compression to increase the local contrast and thus improve detail visibility, but this tends to create artifacts. We developed a local tone mapping method that solves the problems generally encountered by local tone mapping algorithms. Namely, it does not create halo artifacts, nor graying-out of low contrast areas, and provides good color rendition. We then investigated specifically the rendition of color and confirmed that local tone mapping algorithms must be applied to the luminance channel only. We showed that the correlation between luminance and chrominance plays a role in the appearance of the final image but a perfect decorrelation is not necessary. Recently developed HDR monitors enable the display of HDR images with hardly any compression of their dynamic range. The arrival of these displays on the market create the need for new tone mapping algorithms. In particular, legacy images that were mapped to SDR displays must be re-rendered to HDR displays, taking best advantage of the increase in dynamic range. This operation can be seen as the reverse of the tone mapping to SDR. We propose a piecewise linear tone scale function that enhances the brightness of specular highlights so that the sensation of naturalness is improved. Our tone scale algorithm is based on the segmentation of the image into its diffuse and specular components as well as on the range of display luminance that is allocated to the specular component and the diffuse component, respectively. We performed a psychovisual experiment to validate the benefit of our tone scale. The results showed that, with HDR displays, allocating more luminance range to the specular component than what was allocated in the image rendered to SDR displays provides more natural looking images

High Dynamic Range Image Rendering Using a Retinex-Based Adaptive Filter

We propose a new method to render high dynamic range images that models global and local adaptation of the human visual system. Our method is based on the center-surround Retinex model. The novelties of our method is first to use an adaptive surround, whose shape follows the image high contrast edges, thus reducing halo artifacts common to other methods. Secondly, only the luminance channel is processed, which is defined by the first component of a principal component analysis. Principal component analysis provides orthogonality between channels and thus reduces the chromatic changes caused by the modification of luminance. We show that our method efficiently renders high dynamic range images and we compare our results with the current state of the art

Color image enhancement using a Retinex-based adaptive filter

We present a new adaptation of Retinex to enhance the rendering of high dynamic range digital color images. The image is processed using an adaptive Gaussian filter. The shape of the filter basis is adapted to follow the high contrasted edges of the image. In this way, the artifacts introduced by a circularly symmetric filter at the border of high contrasted areas are reduced. This method provides a way of rendering natural images that is inspired by human local adaptation. It is included into a framework that takes raw linear images or radiance maps and outputs 24-bit images rendered for display

Bio-inspired image enhancement for natural color images

Capturing and rendering an image that fulfills the observer's expectations is a difficult task. This is due to the fact that the signal reaching the eye is processed by a complex mechanism before forming a percept, whereas a capturing device only retains the physical value of light intensities. It is especially difficult to render complex scenes with highly varying luminances. For example, a picture taken inside a room where objects are visible through the windows will not be rendered correctly by a global technique. Either details in the dim room will be hidden in shadow or the objects viewed through the window will be too bright. The image has to be treated locally to resemble more closely to what the observer remembers. The purpose of this work is to develop a technique for rendering images based on human local adaptation. We take inspiration from a model of color vision called Retinex. This model determines the perceived color given spatial relationships of the captured signals. Retinex has been used as a computational model for image rendering. In this article, we propose a new solution inspired by Retinex that is based on a single filter applied to the luminance channel. All parameters are image-dependent so that the process requires no parameter tuning. That makes the method more exible than other existing ones. The presented results show that our method suitably enhances high dynamic range images

Digital Camera Workflow for High Dynamic Range Images Using a Model of Retinal Processing

We propose a complete digital camera workflow to capture and render high dynamic range (HDR) static scenes, from RAW sensor data to an output- referred encoded image. In traditional digital camera processing, demosaicing is one of the first operations done after scene analysis. It is followed by rendering operations, such as color correction and tone mapping. Our approach is based on a model of retinal processing of the human visual system (HVS). In the HVS, rendering operations, including adaptation, are performed directly on the cone responses, which corresponds to a mosaic image. Our workflow conforms more closely to the retinal processing model, performing all rendering before demosaicing.. This reduces the complexity of the computation, as only one third of the pixels are processed. This is especially important as our tone mapping operator applies local and global tone corrections, which is usually needed to well render high dynamic scenes. Our algorithms efficiently process HDR images with different keys and different content

Multidimensional image enhancement from a set of unregistered differently exposed images

If multiple images of a scene are available instead of a single image, we can use the additional information conveyed by the set of images to generate a higher quality image. This can be done along multiple dimensions. Super-resolution algorithms use a set of shifted and rotated low resolution images to create a high resolution image. High dynamic range imaging techniques combine images with different exposure times to generate an image with a higher dynamic range. In this paper, we present a novel method to combine both techniques and construct a high resolution, high dynamic range image from a set of shifted images with varying exposure times. We first estimate the camera response function, and convert each of the input images to an exposure invariant space. Next, we estimate the motion between the input images. Finally, we reconstruct a high resolution, high dynamic range image using an interpolation from the non-uniformly sampled pixels. Applications of such an approach can be found in various domains, such as surveillance cameras, consumer digital cameras, etc

Strong EBV-specific CD8+ T-cell response in patients with early multiple sclerosis

Epstein-Barr virus (EBV) has been associated with multiple sclerosis (MS), however, most studies examining the relationship between the virus and the disease have been based on serologies, and if EBV is linked to MS, CD8+ T cells are likely to be involved as they are important both in MS pathogenesis and in controlling viruses. We hypothesized that valuable information on the link between MS and EBV would be ascertained from the study of frequency and activation levels of EBV-specific CD8+ T cells in different categories of MS patients and control subjects. We investigated EBV-specific cellular immune responses using proliferation and enzyme linked immunospot assays, and humoral immune responses by analysis of anti-EBV antibodies, in a cohort of 164 subjects, including 108 patients with different stages of MS, 35 with other neurological diseases and 21 healthy control subjects. Additionally, the cohort were all tested against cytomegalovirus (CMV), another neurotropic herpes virus not convincingly associated with MS, nor thought to be deleterious to the disease. We corrected all data for age using linear regression analysis over the total cohorts of EBV- and CMV-infected subjects. In the whole cohort, the rate of EBV and CMV infections were 99% and 51%, respectively. The frequency of IFN-γ secreting EBV-specific CD8+ T cells in patients with clinically isolated syndrome (CIS) was significantly higher than that found in patients with relapsing-remitting MS (RR-MS), secondary-progressive MS, primary-progressive MS, patients with other neurological diseases and healthy controls. The shorter the interval between MS onset and our assays, the more intense was the EBV-specific CD8+ T-cell response. Confirming the above results, we found that EBV-specific CD8+ T-cell responses decreased in 12/13 patients with CIS followed prospectively for 1.0 ± 0.2 years. In contrast, there was no difference between categories for EBV-specific CD4+ T cell, or for CMV-specific CD4+ and CD8+ T-cell responses. Anti-EBV-encoded nuclear antigen-1 (EBNA-1)-specific antibodies correlated with EBV-specific CD8+ T cells in patients with CIS and RR-MS. However, whereas EBV-specific CD8+ T cells were increased the most in early MS, EBNA-1-specific antibodies were increased in early as well as in progressive forms of MS. Our data show high levels of CD8+ T-cell activation against EBV—but not CMV—early in the course of MS, which support the hypothesis that EBV might be associated with the onset of this diseas

Convergent Evolution of Escape from Hepaciviral Antagonism in Primates

Escape from antagonism by hepatitis C and related viruses has repeatedly evolved in antiviral factor MAVS via convergent evolution, revealing an ancient history of previous viral encounters in primates