Showing papers on "Tone mapping published in 2001"

Contrast enhancement of an image using luminance and RGB statistical metrics

Abstract: An automatic contrast enhancement method improves the quality of an image by increasing the dynamic range of the tone levels in an image without causing an undesirable hue shift. An overall stretch factor that stretches the dynamic range of all the colors is generated based on the standard deviation of the tone levels for the overall luminance of the image. A color weighting factor is used to individually control the amount that each color is stretched. The color weighting factor is based on the difference between the standard deviation of the tone levels for the overall luminance of the image and the standard deviation of the tone levels for each color. An anchor factor is used to preserve the mean tone level for each color while the tone levels far from the mean tone level are changed more dramatically than the tone levels close to the mean tone level, which minimizes hue shifts while maximizing contrast enhancement.

Visual Perception in Realistic Image Synthesis

Abstract: Realism is often a primary goal in computer graphics imagery, and we strive to create images that are perceptually indistinguishable from an actual scene. Rendering systems can now closely approximate the physical distribution of light in an environment. However, physical accuracy does not guarantee that the displayed images will have authentic visual appearance. In recent years the emphasis in realistic image synthesis has begun to shift from the simulation of light in an environment to images that look as real as the physical environment they portray. In other words the computer image should be not only physically correct but also perceptually equivalent to the scene it represents. This implies aspects of the Human Visual System (HVS) must be considered if realism is required. Visual perception is employed in many different guises in graphics to achieve authenticity. Certain aspects of the visual system must be considered to identify the perceptual effects that a realistic rendering system must achieve in order to reproduce effectively a similar visual response to a real scene. This paper outlines the manner in which knowledge about visual perception is increasingly appearing in state-of-the-art realistic image synthesis. After a brief overview of the HVS, this paper is organized into four sections, each exploring the use of perception in realistic image synthesis, each with slightly different emphasis and application. First, Tone Mapping Operators, which attempt to map the vast range of computed radiance values to the limited range of display values, are discussed. Then perception based image quality metrics, which aim to compare images on a perceptual rather than physical basis, are presented. These metrics can be used to evaluate, validate and compare imagery. Thirdly, perception driven rendering algorithms are described. These algorithms focus on embedding models of the HVS directly into global illumination computations in order to improve their efficiency. Finally, techniques for comparing computer graphics imagery against the real world scenes they represent are discussed.

Dynamic range compression based on illumination compensation

Abstract: This paper presents a new approach for effectively compressing the dynamic range of a visual scene while preserving the local contrast in order to reproduce a high quality image on devices with limited dynamic range. In this method, dynamic range compression is performed through a reduction of the illumination effect, by taking into account the characteristics of the human visual system. To precisely extract the illumination component within a reasonable complexity, a multi-scale nonlinear filtering scheme, referred to here as nonlinear multi-scale retinex (NMR), was developed.

Illumination technique for optical dynamic range compression and offset reduction

Abstract: This paper presents a novel illumination technique for image processing in environments which are characterized by large intensity fluctuations and hence a high optical dynamic range (HDR). This proposal shows how by combining a set of images, flashed with different radiant intensities but with a constant exposure time for the imager, a single image can be produced with a compressed dynamic range and a simultaneously reduced offset. This makes it possible to capture high dynamic range scenes without using a high dynamic range camera. This technique can be used as the first signal processing step to simplify the segmentation in applications such as: face recognition, interior surveillance, vehicle occupant detection or motion detection in general.