Tone mapping

About: Tone mapping is a research topic. Over the lifetime, 1713 publications have been published within this topic receiving 48490 citations.

Adaptive tone mapping apparatus and method, and image processing system using the method

Abstract: PURPOSE: An adaptive tone mapping device, a method and an image processing system using the same are provided to prevent contrast ratio damage. CONSTITUTION: A linear log scaling unit(640) performs linear log scaling on brightness map of inputted high dynamic area image. A linear bilateral filtering unit(660) divides the brightness map of the log scaled by using the linear bilateral filtering into a base image and a detail image and extracts the map. An adaptive tone reproducing unit(670) performs dynamic area compression of a basis image by using maximum value and minimum value of the basis image. The adaptive tone reproducing unit adds the compressed basis image and the received detail image.

Automatic face recognition in HDR imaging

Abstract: The gaining popularity of the new High Dynamic Range (HDR) imaging systems is raising new privacy issues caused by the methods used for visualization. HDR images require tone mapping methods for an appropriate visualization on conventional and non-expensive LDR displays. These visualization methods might result in completely different visualization raising several issues on privacy intrusion. In fact, some visualization methods result in a perceptual recognition of the individuals, while others do not even show any identity. Although perceptual recognition might be possible, a natural question that can rise is how computer based recognition will perform using tone mapping generated images? In this paper, a study where automatic face recognition using sparse representation is tested with images that result from common tone mapping operators applied to HDR images. Its ability for the face identity recognition is described. Furthermore, typical LDR images are used for the face recognition training.

A Simple Spatial Tone Mapping Operator for High Dynamic Range Images.

Abstract: We present a simple and effective tone mapping operator, that preserves visibility and contrast impression of high dynamic range images. The method is conceptually simple, and easy to use. We use a s-function type operator which takes into account both the global average of the image, as well as local luminance in the immediate neighborhood of each pixel. The local luminance is computed using a median filter. It is seen that the resulting low dynamic range image preserves fine details, and avoids common artifacts such as halos, gradient reversals or loss of local contrast. Introduction The real world scenes often have a very high range of luminance values. While digital imaging technology now enables us to capture full dynamic range of the real world scene, still we are limited by the low dynamic range displays. Thus the scene can be visualized on a display monitor only after the captured high dynamic range is compressed to available range of the display device. This has been referred to as the tone mapping problem in the literature and a great deal of work has been done in this area by using a mapping that varies spatially depending on the neighborhood of a pixel, often at multiple scales [Pattanaik et.al. 1998; Fattal et.al. 2002;Reinhard et. al 2002; Durand and Dorsey 2002]. [Johnson and Fairchild 2003] have shown how accurate color predictions can be made for tone mapping high dynamic range images. The rendering performance of some of these algorithms has been recently reported in [Kuang et. al 2004]. In this paper we propose a simple tone mapping operator which allows us to preserve the visual content of the real-world scene without the user having to manually set a number of parameters. We show that by using a log of relative luminance at a pixel with respect to its local luminance in a small neighborhood, the standard s-function can be modified to yield visually pleasing results. Further it is also proposed that the local luminance be computed using a median filter, which provides a stronger central indicator than the mean filter. The operator The global contrast helps us to differentiate between various regions of the HDR (high dynamic range) image, which we can loosely classify as dark, dim, lighted, bright etc. Within each region objects become distinguishable due to local contrast against the background – either the object is darker than the background or it is brighter than the background. If the HDR image consisted of only regions of uniform illuminations, the following s-function would compress the range of illumination across the image, to displayable luminance YD in the range 0 -1. YD(x, y) = Y(x, y) / [Y(x, y) + GC] (1) where GC is the global contrast factor computed through

Locally Adaptive Rank-Constrained Optimal Tone Mapping

Abstract: High dynamic range (HDR) tone mapping is formulated as an optimization problem of maximizing perceivable spatial details given the limited dynamic range of display devices. This objective can be attained, as supported by our results, by a novel image display methodology called locally adaptive rank-constrained optimal tone mapping (LARCOTM). The scientific basis for LARCOTM is that the maximum discrimination power of human vision system can only be achieved in a relatively small locality of an image. LARCOTM is fundamentally different from existing HDR tone mapping techniques in that the former can preserve pixel value order statistics within localities in which human foveal vision retains maximum sensitivity, while the latter cannot. As a result, images enhanced by LARCOTM are free of artifacts such as halos and double edges that plague other HDR methods.

Binocular Tone Mapping with Improved Overall Contrast and Local Details

Abstract: Tone mapping is a commonly used technique that maps the set of colors in high-dynamic-range (HDR) images to another set of colors in low-dynamic-range (LDR) images, to fit the need for print-outs, LCD monitors and projectors. Unfortunately, during the compression of dynamic range, the overall contrast and local details generally cannot be preserved simultaneously. Recently, with the increased use of stereoscopic devices, the notion of binocular tone mapping has been proposed in the existing research study. However, the existing research lacks the binocular perception study and is unable to generate the optimal binocular pair that presents the most visual content. In this paper, we propose a novel perception-based binocular tone mapping method, that can generate an optimal binocular image pair (generating left and right images simultaneously) from an HDR image that presents the most visual content by designing a binocular perception metric. Our method outperforms the existing method in terms of both visual and time performance.