Expanding low dynamic range videos for high dynamic range applications

Abstract

In this paper we introduce an algorithm and related methods that expand the contrast range of Low Dynamic Range (LDR) videos in order to regenerate missing High Dynamic Range (HDR) data. For content generated from single exposure LDR sequences, this is clearly an under constrained problem. We achieved the expansion by inverting established tone mapping operator, a process we term inverse tone mapping. This approach is augmented by a number of methods which help expand the luminance for the required pixels while avoiding artifacts. These methods may be used to convert the large libraries of available legacy LDR content for use, for instance, on new content-starved HDR devices. Moreover, these same methods may be used to provide animated emissive surfaces for image based lighting (IBL). We demonstrate results for all the above applications and validate the resultant HDR videos with original HDR references using the HDR Visual Difference Predictor (HDR-VDP) image metric.

Evaluation of reverse tone mapping through varying exposure conditions

“…They then produce a so-called expand-map by density estimation of the bright areas, and use this map to interpolate between the LDR image and the initial inverse tone mapped HDR image, thus modulating the expansion range. This framework has been extended to video by designing a temporally-coherent version of the expand-map [Banterle et al 2008]. The LDR2HDR framework of Rempel et al [2007] is similar in spirit, but their expand-map (which they term brightness enhancement function) can be computed in real time using the GPU.…”

Dynamic range expansion of video sequences: A subjective quality assessment study

“…In a more constrained scenario, where the goal is to render LDR content on an HDR screen, the problem is more tractable, though its solution is not unique. As a result, various expansion operators (EOs) have been proposed [2][3][4][5][6][7][8][9][10]. Evaluating these techniques plays a key role in the design of new EOs and helps to improve the characteristics of HDR displays.…”

The high dynamic range imaging pipeline : Tone-mapping, distribution, and single-exposure reconstruction

“…Banterle et al [24,25] used the median cut algorithm in order to derive an expand map for boosting highlights. The method was also extended for video processing and with cross-bilateral filtering of the expand map [26]. Another expand map method was presented by Rempel et al [214], which simplifies the estimation using a Gaussian filter for real-time performance.…”