Showing papers on "Tone mapping published in 2002"

Fast bilateral filtering for the display of high-dynamic-range images

Abstract: We present a new technique for the display of high-dynamic-range images, which reduces the contrast while preserving detail. It is based on a two-scale decomposition of the image into a base layer,...

Photographic tone reproduction for digital images

Abstract: A classic photographic task is the mapping of the potentially high dynamic range of real world luminances to the low dynamic range of the photographic print. This tone reproduction problem is also faced by computer graphics practitioners who map digital images to a low dynamic range print or screen. The work presented in this paper leverages the time-tested techniques of photographic practice to develop a new tone reproduction operator. In particular, we use and extend the techniques developed by Ansel Adams to deal with digital images. The resulting algorithm is simple and produces good results for a wide variety of images.

Fast bilateral filtering for the display of high-dynamic-range images

Abstract: We present a new technique for the display of high-dynamic-range images, which reduces the contrast while preserving detail. It is based on a two-scale decomposition of the image into a base layer, encoding large-scale variations, and a detail layer. Only the base layer has its contrast reduced, thereby preserving detail. The base layer is obtained using an edge-preserving filter called the bilateral filter. This is a non-linear filter, where the weight of each pixel is computed using a Gaussian in the spatial domain multiplied by an influence function in the intensity domain that decreases the weight of pixels with large intensity differences. We express bilateral filtering in the framework of robust statistics and show how it relates to anisotropic diffusion. We then accelerate bilateral filtering by using a piecewise-linear approximation in the intensity domain and appropriate subsampling. This results in a speed-up of two orders of magnitude. The method is fast and requires no parameter setting.

Gradient domain high dynamic range compression

Abstract: We present a new method for rendering high dynamic range images on conventional displays. Our method is conceptually simple, computationally efficient, robust, and easy to use. We manipulate the gradient field of the luminance image by attenuating the magnitudes of large gradients. A new, low dynamic range image is then obtained by solving a Poisson equation on the modified gradient field. Our results demonstrate that the method is capable of drastic dynamic range compression, while preserving fine details and avoiding common artifacts, such as halos, gradient reversals, or loss of local contrast. The method is also able to significantly enhance ordinary images by bringing out detail in dark regions.

Photographic tone reproduction for digital images

Abstract: A classic photographic task is the mapping of the potentially high dynamic range of real world luminances to the low dynamic range of the photographic print. This tone reproduction problem is also ...

Gradient domain high dynamic range compression

Abstract: We present a new method for rendering high dynamic range images on conventional displays. Our method is conceptually simple, computationally efficient, robust, and easy to use. We manipulate the gr...

A tone mapping algorithm for high contrast images

Abstract: A new method is presented that takes as an input a high dynamic range image and maps it into a limited range of luminance values reproducible by a display device. There is significant evidence that a similar operation is performed by early stages of human visual system (HVS). Our approach follows functionality of HVS without attempting to construct its sophisticated model. The operation is performed in three steps. First, we estimate local adaptation luminance at each point in the image. Then, a simple function is applied to these values to compress them into the required display range. Since important image details can be lost during this process, we then re-introduce details in the final pass over the image.

Tone Reproduction and Physically Based Spectral Rendering

Abstract: The ultimate aim of realistic graphics is the creation of images that provoke the same responses that a viewer would have to a real scene. This STAR addresses two related key problem areas in this effort which are located at opposite ends of the rendering pipeline, namely the data structures used to describe light during the actual rendering process, and the issue of displaying such radiant intensities in a meaningful way. The interest in the first of these subproblems stems from the fact that it is common industry practice to use RGB colour values to describe light intensity and surface reflectancy. While viable in the context of methods that do not strive to achieve true realism, this approach has to be replaced by more physically accurate techniques if a prediction of nature is intended. The second subproblem is that while research into ways of rendering images provides us with better and faster methods, we do not necessarily see their full effect due to limitations of the display hardware. The low dynamic range of a standard computer monitor requires some form of mapping to produce images that are perceptually accurate. Tone reproduction operators attempt to replicate the effect of real-world luminance intensities. This STAR report will review the work to date on spectral rendering and tone reproduction techniques. It will include an investigation into the need for spectral imagery synthesis methods and accurate tone reproduction, and a discussion of major approaches to physically correct rendering and key tone mapping algorithms. The future of both spectral rendering and tone reproduction techniques will be considered, together with the implications of advances in display hardware.

Meet iCAM: A Next-Generation Color Appearance Model

Abstract: For over 20 years, color appearance models have evolved to the point of international standardization These models are capable of predicting the appearance of spatially-simple color stimuli under a wide variety viewing conditions and have been applied to images by treating each pixel as an independent stimulus It has been more recently recognized that revolutionary advances in color appearance modeling would require more rigorous treatment of spatial (and perhaps temporal) appearance phenomena In addition, color appearance models are often more complex than warranted by the available visual data and limitations in the accuracy and precision of practical viewing conditions Lastly, issues of color difference measurement are typically treated separate from color appearance Thus, the stage has been set for a new generation of color appearance models This paper presents one such model called iCAM, for image color appearance model The objectives in formulating iCAM were to simultaneously provide traditional color appearance capabilities, spatial vision attributes, and color difference metrics, in a model simple enough for practical applications The framework and initial implementation of the model are presented along with examples that illustrate its performance for chromatic adaptation, appearance scales, color difference, crispening, spreading, high-dynamic-range tone mapping, and image quality measurement It is expected that the implementation of this model framework will be refined in the coming years as new data become available

System and method for digital image tone mapping using an adaptive sigmoidal function based on perceptual preference guidelines

Abstract: An adaptive image tone mapping curve based on perceptual preference guidelines is generated as a sigmoidal function, in which the sigmoidal function parameters (slope and shift) are determined by original image statistics. Tone curves generated for different images each have a smooth sigmoidal shape, so that the tone mapping process does not change the image histogram shape drastically. The sigmoidal function has the form: t ⁢ ( x ) = 100 1 + exp ⁢ ( - α ⁢ ( x / 100 - β ) ) , where α is the slope parameter and β is the shift parameter. The input value x in the sigmoidal function varies in the range [0, 100], because the tone curve is generated on an L* scale, which has values from 0 to 100. The sigmoidal tone curve calculation can be implemented efficiently using simple arithmetic operations by pre-calculating and storing various factors used in the calculation of α and β and by pre-generating a pair of fixed tone curves with two extreme slopes and interpolating between the curves.

Adaptive gain control for high dynamic range image display

Abstract: Realistic display of high dynamic range images without introducing any artifact is a hard problem. In this paper we address this problem using a detail preserving local gain control approach. Unlike many other local gain control methods available in the literature, our method is simple, and does not introduce ugly "halo" artifacts around the high dynamic range edges. We demonstrate the usefulness of this method by showing several examples.

High Dynamic Range Imaging of Natural Scenes.

Abstract: The ability to capture and render high dynamic range scenes limits the quality of current consumer and professional digital cameras. The absence of a well-calibrated high dynamic range color image database of natural scenes is an impediment to developing such rendering algorithms for digital photography. This paper describes our efforts to create such a database. First, we discuss how the image dynamic range is affected by three main components in the imaging pipeline: the optics, the sensor and the color transformation. Second, we describe a calibrated, portable high dynamic range imaging system. Third, we discuss the general properties of seventy calibrated high dynamic range images of natural scenes in the database (http://pdc.stanford.edu/hdri/). We recorded the calibrated RGB values and the spectral power distribution of illumination at different locations for each scene. The scene luminance ranges span two to six orders of magnitude. Within any scene, both the absolute level and the spectral composition of the illumination vary considerably. This suggests that future high dynamic range rendering algorithms need to account jointly for local color adaptation and local illumination level.

Perceptual Evaluation of Tone Mapping Operators with Regard to Similarity and Preference

Abstract: For years, 24-bit images effectively using 256 values for each color channel wereconsidered accurate enough to be used in the creation and display of photorealisticimagery. On the other end, photographers knowing the limitation of cameras andfilms would never attempt to photograph a scene including a light source placed inthe camera’s field of vision. However, as a result of global illumination renderingand high dynamic range (HDR) imaging [DM97], it is now common to generateimages spanning a huge range of luminance. Dealing with such images in elec-tronic form requires extending file formats that are restricted to too few luminancevalues and colors. An even more serious issue is effective displaying/printing ofthose images using media with limited dynamic range (both in reproducible lumi-nance values and color gamut).The first limitation was successfully addressed in different pixel encoding for-mats. A simple approach relies on using three floating point numbers for eachpixel RGB values, however, this leads to excessive file sizes. The HDR imagesize can be reduced to four bytes for each pixel using the RGBE format [War91],in which a common exponent and a mantissa are assumed for each channel thusallowing a wide dynamic range with little storage overhead. Another format, thelogLuv encoding for tiff images [Lar98] separates a logarithmic representation ofluminance and aCIE

Automatic tone mapping for images

Abstract: An image processing method for processing image data comprises the steps of obtaining scanpath data corresponding to original image data, determining regions of interest for the original image data based on the obtained scanpath data, and mapping tone values of the original image data corresponding to each region of interest in order to obtain tone-mapped image data.

Perceptual tone mapping operators for high dynamic range scenes

Abstract: A major goal of realistic image synthesis is to generate images that are both physically and perceptually indistinguishable from reality. One of the practical obstacles in reaching this goal is that the natural world exhibits a wide range of colors and intensities. The range of the luminances in the real world can vary from 10-4cd/m2 (for starlight) to 105cd/m2 (for a daylight scene). Reproducing these luminances on a cathode-ray tube (CRT) display is currently not possible as the achievable intensities are about 100 cd/m2 and the practical ratio between maximum and minimum pixel intensity is approximately 100:1. At the University of Bristol, we have constructed a High Dynamic Range (HDR) viewer that is capable of achieving a 10,000:1 contrast ratio. This sketch investigates, by means of psychophysical experiments, the benefits such a HDR device has to offer realistic computer graphics.

Visualization of high dynamic range images

Abstract: A novel paradigm for information visualization in high dynamic range images is presented. These images, real or synthetic, have luminance with typical ranges many orders of magnitude higher than that of standard output devices, thereby requiring some processing for their visualization. In contrast to existing approaches, which compute a single image with reduced range, close in a given sense to the original data, we propose to look for a representative set of images. The goal is then to produce a minimal set of images capturing the information all over the high dynamic range data, while at the same time preserving a natural appearance for each one of the images in the set. A specific algorithm that achieves this goal is presented and tested on natural and synthetic data.

Automatic digital picture enhancement

Abstract: A method and apparatus for enhancing a digital image. First, human faces are located (201) within a digital image. The digital image is then analyzed (202), including analysis of the regions determined to be human faces and the analysis of the digital image as a whole. A tone mapping function (311) is then determined for enhancing the image quality of the digital image. The tone mapping function is determined using both the analysis of detected faces and the analysis of the image as a whole to obtain a tone mapping function that incorporates both psychological factors (e.g., average face region lightness and average picture lightness) and signal factors (e.g., digital resolution, face region contrast, histogram uniformity,and noise issue). The tone mapping function is then applied (313) to the digital image so as to produce an enhanced digital image. The present invention is automatic and does not require that the user provide any input. In addition, because the method and apparatus of the present invention incorporates both psychological factors and signal factors, the resulting enhanced images are perceived to be of good image quality.

Rating Tone-Mapping Algorithms for Gradations.

Abstract: We propose an experiment to rate the merit of four algorithms in achieving satisfactory tone-mapping. The appearance of a unique scene including luminance gradations and a wide distribution of luminance patches has been evaluated in both real and simulated situations by the same observers. The real scene consisted of a wide wall receiving controlled illumination. The test consisted of two horizontal gradations of grey with different gamma values, embedded in an achromatic noise background of high spatial frequency. Each observer was invited to choose the gradation he found “optimal”. The simulation was produced on a calibrated CRT display. Four tonemapping algorithms were implemented, three of which were linear, to render the simulated conditions. With the real scene, observers are able to judge accurately which gradation is the best representative of the optimal gamma. Under examination of the distribution of preferred choice around the optimal gamma, it seems that the rating of gamma values is about symmetric on a logarithmic gamma scale. The hypothesis is that a tone-mapping algorithm which performs well should yield the same optimal gamma as in the reality. After our experiments, it appears that the four algorithms which were tested fall in two classes, either underor over-estimating the gamma values. Despite inter-observer variability, observers agree on their judgement.