Showing papers on "Tone mapping published in 2006"

High dynamic range image rendering with a retinex-based adaptive filter

Abstract: 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 filter, whose shape follows the image high-contrast edges, thus reducing halo artifacts common to other methods. Second, 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

Interactive local adjustment of tonal values

Abstract: This paper presents a new interactive tool for making local adjustments of tonal values and other visual parameters in an image. Rather than carefully selecting regions or hand-painting layer masks, the user quickly indicates regions of interest by drawing a few simple brush strokes and then uses sliders to adjust the brightness, contrast, and other parameters in these regions. The effects of the user's sparse set of constraints are interpolated to the entire image using an edge-preserving energy minimization method designed to prevent the propagation of tonal adjustments to regions of significantly different luminance. The resulting system is suitable for adjusting ordinary and high dynamic range images, and provides the user with much more creative control than existing tone mapping algorithms. Our tool is also able to produce a tone mapping automatically, which may serve as a basis for further local adjustments, if so desired. The constraint propagation approach developed in this paper is a general one, and may also be used to interactively control a variety of other adjustments commonly performed in the digital darkroom.

A perceptual framework for contrast processing of high dynamic range images

Abstract: Image processing often involves an image transformation into a domain that is better correlated with visual perception, such as the wavelet domain, image pyramids, multiscale-contrast representations, contrast in retinex algorithms, and chroma, lightness, and colorfulness predictors in color-appearance models. Many of these transformations are not ideally suited for image processing that significantly modifies an image. For example, the modification of a single band in a multiscale model leads to an unrealistic image with severe halo artifacts. Inspired by gradient domain methods, we derive a framework that imposes constraints on the entire set of contrasts in an image for a full range of spatial frequencies. This way, even severe image modifications do not reverse the polarity of contrast. The strengths of the framework are demonstrated by aggressive contrast enhancement and a visually appealing tone mapping, which does not introduce artifacts. In addition, we perceptually linearize contrast magnitudes using a custom transducer function. The transducer function has been derived especially for the purpose of HDR images, based on the contrast-discrimination measurements for high-contrast stimuli.

Inverse tone mapping

Abstract: In recent years many Tone Mapping Operators (TMOs) have been presented in order to display High Dynamic Range Images (HDRI) on typical display devices. TMOs compress the luminance range while trying to maintain contrast. The dual of tone mapping, inverse tone mapping, expands a Low Dynamic Range Image (LDRI) into a HDRI. HDRIs contain a broader range of physical values that can be perceived by the human visual system. The majority of today's media is stored in low dynamic range. Inverse Tone Mapping Operators (iTMOs) could thus potentially revive all of this content for use in high dynamic range display and image-based lighting. We propose an approximate solution to this problem that uses median-cut to find the areas considered of high luminance and subsequently apply a density estimation to generate an Expand-map in order to extend the range in the high luminance areas using an inverse Photographic Tone Reproduction operator.

Backward compatible high dynamic range MPEG video compression

Abstract: To embrace the imminent transition from traditional low-contrast video (LDR) content to superior high dynamic range (HDR) content, we propose a novel backward compatible HDR video compression (HDR MPEG) method. We introduce a compact reconstruction function that is used to decompose an HDR video stream into a residual stream and a standard LDR stream, which can be played on existing MPEG decoders, such as DVD players. The reconstruction function is finely tuned to the content of each HDR frame to achieve strong decorrelation between the LDR and residual streams, which minimizes the amount of redundant information. The size of the residual stream is further reduced by removing invisible details prior to compression using our HDR-enabled filter, which models luminance adaptation, contrast sensitivity, and visual masking based on the HDR content. Designed especially for DVD movie distribution, our HDR MPEG compression method features low storage requirements for HDR content resulting in a 30% size increase to an LDR video sequence. The proposed compression method does not impose restrictions or modify the appearance of the LDR or HDR video. This is important for backward compatibility of the LDR stream with current DVD appearance, and also enables independent fine tuning, tone mapping, and color grading of both streams.

Image Attributes and Quality for Evaluation of Tone Mapping Operators

Abstract: The problem of reproducing high dynamic range images on devices with restricted dynamic range has gained a lot of interest in the computer graphics community. There exist various approaches to this issue, which span several research areas including computer graphics, image processing, color science, physiology, neurology, psychology, etc. These approaches assume a thorough knowledge of both the objective and subjective attributes of an image. However, no comprehensive overview and analysis of such attributes has been published so far. In this paper, we present an overview of image quality attributes of different tone mapping methods. Furthermore, we propose a scheme of relationships between these attributes, leading to the definition of an overall image quality measure. We present results of subjective psychophysical tests that we have performed to prove the proposed relationship scheme. We also present the evaluation of existing tone mapping methods with regard to these attributes. Our effort is not just useful to get into the tone mapping field or when implementing a tone mapping operator, but it also sets the stage for well-founded quality comparisons between tone mapping operators. By providing good definitions of the different attributes, user-driven or fully automatic comparisons are made possible at all.

Color appearance in high-dynamic-range imaging

Abstract: When viewing images on a monitor, we are adapted to the lighting conditions of our viewing environment as well as the monitor itself, which can be very different from the lighting conditions in which the images were taken. As a result, our perception of these photographs depends directly on the environment in which they are displayed. For high-dynamic-range images, the disconnect in the perception of scene and viewing environments is potentially much larger than in conventional film and photography. To prepare an im- age for display, luminance compression alone is therefore not suffi- cient. We propose to augment current tone reproduction operators with the application of color appearance models as an independent preprocessing step to preserve chromatic appearance across scene and display environments. The method is independent of any spe- cific tone reproduction operator and color appearance model (CAM) so that for each application the most suitable tone reproduction op- erator and CAM can be selected. © 2006 SPIE and

Encoding of high dynamic range video with a model of human cones

Abstract: A recently developed quantitative model describing the dynamical response characteristics of primate cones is used for rendering high dynamic range (HDR) video. The model provides range compression, as well as luminance-dependent noise suppression. The steady-state (static) version of the model provides a global tone mapping algorithm for rendering HDR images. Both the static and dynamic cone models can be inverted, enabling expansion of the HDR images and video that were compressed with the cone model.

Analysis of Reproducing Real-World Appearance on Displays of Varying Dynamic Range

Abstract: We conduct a series of experiments to investigate the desired properties of a tone mapping operator (TMO) and to design such an operator based on subjective data. We propose a novel approach to the tone mapping problem, in which the tone mapping parameters are determined based on the data from subjective experiments, rather than an image processing algorithm or a visual model. To collect this data, a series of experiments are conducted in which the subjects adjust three generic TMO parameters: brightness, contrast and color saturation. In two experiments, the subjects are to nd a) the most preferred image without a reference image (preference task) and b) the closest image to the real-world scene which the subjects are confronted with (delity task). We analyze subjects’ choice of parameters to provide more intuitive control over the parameters of a tone mapping operator. Unlike most of the researched TMOs that focus on rendering for standard low dynamic range monitors, we consider a broad range of potential displays, each offering different dynamic range and brightness. We simulate capabilities of such displays on a high dynamic range (HDR) display. This allows us to address the question of how tone mapping needs to be adjusted to accommodate displays with drastically different dynamic ranges.

Beyond Tone Mapping: Enhanced Depiction of Tone Mapped HDR Images

Abstract: High Dynamic Range (HDR) images capture the full range of luminance present in real world scenes, and unlike Low Dynamic Range (LDR) images, can simultaneously contain detailed information in the deepest of shadows and the brightest of light sources. For display or aesthetic purposes, it is often necessary to perform tone mapping, which creates LDR depictions of HDR images at the cost of contrast information loss. The purpose of this work is two-fold: to analyze a displayed LDR image against its original HDR counterpart in terms of perceived contrast distortion, and to enhance the LDR depiction with perceptually driven colour adjustments to restore the original HDR contrast information. For analysis, we present a novel algorithm for the characterization of tone mapping distortion in terms of observed loss of global contrast, and loss of contour and texture details. We classify existing tone mapping operators accordingly. We measure both distortions with perceptual metrics that enable the automatic and meaningful enhancement of LDR depictions. For image enhancement, we identify artistic and photographic colour techniques from which we derive adjustments that create contrast with colour. The enhanced LDR image is an improved depiction of the original HDR image with restored contrast information.

Analysis of Reproducing Real-World Appearance on Displays of Varying Dynamic Range

Abstract: We conduct a series of experiments to investigate the desired properties of a tone mapping operator (TMO) and to design such an operator based on subjective data. We propose a novel approach to the tone mapping problem, in which the tone mapping parameters are determined based on the data from subjective experiments, rather than an image processing algorithm or a visual model. To collect this data, a series of experiments are conducted in which the subjects adjust three generic TMO parameters: brightness, contrast and color saturation. In two experiments, the subjects are to nd a) the most preferred image without a reference image (preference task) and b) the closest image to the real-world scene which the subjects are confronted with (delity task). We analyze subjects’ choice of parameters to provide more intuitive control over the parameters of a tone mapping operator. Unlike most of the researched TMOs that focus on rendering for standard low dynamic range monitors, we consider a broad range of potential displays, each offering different dynamic range and brightness. We simulate capabilities of such displays on a high dynamic range (HDR) display. This allows us to address the question of how tone mapping needs to be adjusted to accommodate displays with drastically different dynamic ranges.

Tone Mapping for HDR Image using Optimization A New Closed Form Solution

Abstract: This paper studies an optimization approach for designing tone reproduction curve (TRC) based tone mapping operators for the display of high dynamic range (HDR) images in low dynamic range (LDR) reproduction media. Previous work has shown that the tone mapping problem can be formulated as that of optimizing a two-term cost function where adjusting the relative weightings of the two terms allows users to interactively control the appearance of the output image. However, only heuristic solutions to the tone mapping objective function have been found in past research. The main contribution of this paper is the re-formulation of the objective function to allow the introduction of a closed-form solution to the two-term tone mapping objective function. The new solution has simplified previous heuristic solutions and made this approach mathematically more elegant, computationally faster and practically easier to implement

Dynamic range optimization by local contrast correction and histogram image analysis

Abstract: The original dynamic range of a scene is generally constrained into the smaller dynamic range of the acquisition system. This results in the difficulty to design a global tone correction that permits to discriminate both shadow and highlight details. In this work we present a local contrast correction algorithm that allows for simultaneous shadow and highlight adjustments, starting from a simple pixel-wise "gamma" correction, piloted by image statistics analysis.

HDR VolVis: high dynamic range volume visualization

Abstract: In this paper, we present an interactive high dynamic range volume visualization framework (HDR VolVis) for visualizing volumetric data with both high spatial and intensity resolutions. Volumes with high dynamic range values require high precision computing during the rendering process to preserve data precision. Furthermore, it is desirable to render high resolution volumes with low opacity values to reveal detailed internal structures, which also requires high precision compositing. High precision rendering will result in a high precision intermediate image (also known as high dynamic range image). Simply rounding up pixel values to regular display scales will result in loss of computed details. Our method performs high precision compositing followed by dynamic tone mapping to preserve details on regular display devices. Rendering high precision volume data requires corresponding resolution in the transfer function. To assist the users in designing a high resolution transfer function on a limited resolution display device, we propose a novel transfer function specification interface with nonlinear magnification of the density range and logarithmic scaling of the color/opacity range. By leveraging modern commodity graphics hardware, multiresolution rendering techniques and out-of-core acceleration, our system can effectively produce an interactive visualization of large volume data, such as 2.048/sup 3/.

Computational Model of Lightness Perception in High Dynamic Range Imaging

Abstract: An anchoring theory of lightness perception by Gilchrist et al. [1999] explains many characteristics of human visual system such as lightness constancy and its spectacular failures which are important in the perception of images. The principal concept of this theory is the perception of complex scenes in terms of groups of consistent areas (frameworks). Such areas, following the gestalt theorists, are defined by the regions of common illumination. The key aspect of the image perception is the estimation of lightness within each framework through the anchoring to the luminance perceived as white, followed by the computation of the global lightness. In this paper we provide a computational model for automatic decomposition of HDR images into frameworks. We derive a tone mapping operator which predicts lightness perception of the real world scenes and aims at its accurate reproduction on low dynamic range displays. Furthermore, such a decomposition into frameworks opens new grounds for local image analysis in view of human perception.

Tone mapping for high dynamic range images

Abstract: 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.

Nonlinear enhancement of extremely high contrast images for visibility improvement

Abstract: This paper presents a novel image enhancement algorithm using a multilevel windowed inverse sigmoid (MWIS) function for rendering images captured under extremely non uniform lighting conditions. MWIS based image enhancement is a combination of three processes viz. adaptive intensity enhancement, contrast enhancement and color restoration. Adaptive intensity enhancement uses the non linear transfer function to pull up the intensity of underexposed pixels and to pull down the intensity of overexposed pixels of the input image. Contrast enhancement tunes the intensity of each pixel's magnitude with respect to its surrounding pixels. A color restoration process based on relationship between spectral bands and the luminance of the original image is applied to convert the enhanced intensity image back to a color image.

Methods and Systems for Tone Mapping Messaging

Abstract: Embodiments of the present invention comprise methods and systems for signaling tone map data to an image recipient.

Tone reproduction in color imaging systems by histogram equalization of macro edges

Abstract: Tone reproduction attempts to scale or map high dynamic range image data such that the resulting image has preserved the visual brightness and better contrast impression of the original scenes. In this paper, we propose a systematic approach to tone reproduction by histogram equalization of macro edges. The proposed approach has been integrated with a robust image processing pipeline, and the experimental results show that the proposed algorithm is very stable for accommodating diverse illuminants and scenes.

symTone: two-handed manipulation of tone reproduction curves

Abstract: We present symTone, a dual-mouse, symmetric image manipulation application. symTone includes a symmetric method for manipulating a tone reproduction curve using two standard USB mice. The symTone technique is an important contribution because the two mice are manipulating a geometric object as a tool to improve the underlying digital image, thus a spatial object (the curve) is being used to manipulate non-spatial data (the image tones). Our empirical evaluation of the technique shows that symmetric interaction can be effective for manipulating non-spatial data. This novel technique offers a significant improvement in ease of use and is a precursor to more advanced symmetric tone-mapping applications.

HDR CFA image rendering

Abstract: We propose a method for high dynamic range (HDR) mapping that is directly applied on the color filter array (CFA) image instead of the already demosaiced image. This rendering is closer to retinal processing where an image is acquired by a mosaic of cones and where adaptive non-linear functions apply before interpolation. Thus, in our framework, demosaicing is the final step of the rendering. Our method, inspired by retinal sampling and adaptive processing is very simple, fast because only one third of operations are needed, and gives good result as shown by experiments.

Nonlinear image enhancement to improve face detection in complex lighting environment

Abstract: A robust and efficient image enhancement technique has been developed to improve the visual quality of digital images that exhibit dark shadows due to the limited dynamic ranges of imaging and display devices which are incapable of handling high dynamic range scenes. The proposed technique processes images in two separate steps: dynamic range compression and local contrast enhancement. Dynamic range compression is a neighborhood dependent intensity transformation which is able to enhance the luminance in dark shadows while keeping the overall tonality consistent with that of the input image. The image visibility can be largely and properly improved without creating unnatural rendition in this manner. A neighborhood dependent local contrast enhancement method is used to enhance the images contrast following the dynamic range compression. Experimental results on the proposed image enhancement technique demonstrates strong capability to improve the performance of convolutional face finder compared to histogram equalization and multiscale Retinex with color restoration without compromising the false alarm rate.

Computational model of lightness perception in high dynamic range imaging

Abstract: An anchoring theory of lightness perception by Gilchrist et al. [1999] explains many characteristics of human visual system such as lightness constancy and its spectacular failures which are important in the perception of images. The principal concept of this theory is the perception of complex scenes in terms of groups of consistent areas (frameworks). Such areas, following the gestalt theorists, are defined by the regions of common illumination. The key aspect of the image perception is the estimation of lightness within each framework through the anchoring to the luminance perceived as white, followed by the computation of the global lightness. In this paper we provide a computational model for automatic decomposition of HDR images into frameworks. We derive a tone mapping operator which predicts lightness perception of the real world scenes and aims at its accurate reproduction on low dynamic range displays. Furthermore, such a decomposition into frameworks opens new grounds for local image analysis in view of human perception.

Dynamic range compression of high dynamic range imagery

Abstract: An improved apparatus and method adaptively compresses the dynamic range of an image from a sensor by rescaling the value of every pixel to fit within the dynamic range of a low dynamic range display while preserving local image contrast and global scene appearance.

Fuzzy Based Brightness Compensation for High Dynamic Range Images

Abstract: The high dynamic range of illumination may cause serious distortions and problems in the view and further processing of digital images. In this paper a new fuzzy based tone reproduction pre-processing algorithm is introduced which may help in developing the hardly or non viewable features and content of the images making easier the further processing of it.

High dynamic range material color applying drawing method

Abstract: A material quality exaggeration-plotting method of high dynamic scope includes carrying out light shining and setting up material quality model, making light exaggeration on each pixel by utilizing programmable exaggeration flow line based on GPU, outputting exaggeration result to float point frame buffer storage region, simulating lens dazzle effect to let user sense light intensity of high brightness object, displaying scene image in high dynamic scope on screen in low dynamic scope based on GPU tone mapping algorithm and keeping original tone.

Fine feature preservation in HDR tone mapping

Abstract: We present a High Dynamic Range (HDR) tone-mapping technique that preserves “fine” image features that have significantly different luminances than their surround, most notably sharp specular highlights and pronounced textures. Many HDR tone-mapping algorithms have been introduced to solve the general problem of mapping a real world dynamic range, on the order of 1:100,000, to a display range, on the order of 1:256. In this work, we focus on enhancing the family of tone-mapping techniques described in [Durand and Dorsey 2002], which utilize bilateral filtering.

Contrast-gain-based visual tone mapping for digital photo prints

Abstract: With the popularization of digital photo printing, there is a demand for print image quality that approaches the quality of silver halide photographs. One way to achieve this is through automatic correction of image luminance/tone. The conventional approach based on spatially invariant mapping often causes undesired luminance changes' when enhancing contrast; moreover, luminance changes are also accompanied by changes in contrast. This paper proposes a novel algorithm for the enhancement of the contrast and lightness using spatially variant mapping to achieve high-quality printing of images photographed using digital cameras. First, we define a "contrast-gain" function to quantitatively evaluate the visual contrast that results from tone mapping. Based on this function, the proposed tone mapping algorithm enables independent control of the lightness and contrast through spatially variant processing. Next, we formalize a "shadow-up tone curve," which produces an effect similar to auxiliary lighting during photography. Our contrast-gain-based visual tone mapping method, which uses the shadow-up tone curve in the algorithm, has none of the unnaturalness that arises with a conventional single tone curve. Furthermore, it provides an extremely natural effect similar to that in images photographed by a professional photographer using auxiliary light provided by a reflection board.

The Human Visual System and HDR Tone Mapping

Abstract: The dynamic range of illumination in a real-world scene is high—on the order of 10,000 to 1 from highlights to shadows, and higher if light sources are directly visible. A much larger range of illumination can also occur if the scene includes both an outdoor area illuminated by sunlight and an indoor area illuminated by interior light. This chapter proposes the view that the modeling of human visual adaptation is the key to realistic tone mapping of HDR images. It is shown that photoreceptor adaptation is the most important factor responsible for visual adaptation. The relation between various tone-mapping algorithms and the photoreceptor adaptation model is made evident. Background intensity is a key component in this model. Some of the commonly used methods for computing this background intensity in images were discussed. The usefulness of a human visual model was also seen in realistic simulation of visual effects associated with the wide range of real-life illuminations. This chapter explores the similarities between several current tone-reproduction operators.

Networked document imaging with normalization and optimization

Abstract: A system architecture is presented for document imaging in an open, distributed environment over networks, where various kinds of imaging devices can be interconnected remotely. The key components are two sets of image processing operations to transform input images to (1) canonical image representations to absorb different visual appearance due to characteristics of imaging devices or image acquisition conditions (normalization), and (2) optimal image representations according to tasks and preferences of individual users (optimization). Images captured through a diversity of input devices can be delivered to remote sites through networks, and then will be used for a variety of tasks such as printing on paper sheets, browsing on displays, and editing. These diversities can be resolved systematically by placing the normalizations at an upper end (routing servers) and the optimizations at a lower end (clients) of the data flow over networks. In view of this architecture, we describe some instances of the normalizations and optimizations associated with a particular task of highly legible printing of scanned document images. Three essential algorithms are mentioned for optimizing document images: adaptive tone mapping with background cleaning, text super-resolution, and text color clustering. The optimization process is mentioned for highly legible printing, along with some other potential applications and tasks.