A visibility matching tone reproduction operator for high dynamic range scenes

Larson, Gregory Ward; Rushmeier, Holly; Piatko, Christine D.

doi:10.1109/2945.646233

Cited by 620 publications

(156 citation statements)

References 20 publications

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“…[10] performed this process through quantization, [16] through histogram adjustment, and [30] through a form of anisotropic diffusion. [21] modeled the effect of visual adaptation in viewing high-dynamic range images, and later work [22] modeled global time-dependent effects.…”

Section: Related Workmentioning

confidence: 99%

Real-Time High-Dynamic Range Texture Mapping

Cohen¹,

Tchou²,

Hawkins³

et al. 2001

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Abstract. This paper presents a technique for representing and displaying high dynamic-range texture maps (HDRTMs) using current graphics hardware. Dynamic range in real-world environments often far exceeds the range representable in 8-bit per-channel texture maps. The increased realism afforded by a highdynamic range representation provides improved fidelity and expressiveness for interactive visualization of image-based models. Our technique allows for realtime rendering of scenes with arbitrary dynamic range, limited only by available texture memory. In our technique, high-dynamic range textures are decomposed into sets of 8-bit textures. These 8-bit textures are dynamically reassembled by the graphics hardware's programmable multitexturing system or using multipass techniques and framebuffer image processing. These operations allow the exposure level of the texture to be adjusted continuously and arbitrarily at the time of rendering, correctly accounting for the gamma curve and dynamic range restrictions of the display device. Further, for any given exposure only two 8-bit textures must be resident in texture memory simultaneously. We present implementation details of this technique on various 3D graphics hardware architectures. We demonstrate several applications, including high-dynamic range panoramic viewing with simulated auto-exposure, real-time radiance environment mapping, and simulated Fresnel reflection.

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Section: Related Workmentioning

confidence: 99%

Real-Time High-Dynamic Range Texture Mapping

Cohen¹,

Tchou²,

Hawkins³

et al. 2001

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“…Conversely, if something is not visible on the display, we want to say that it would not be visible to an observer in the actual scene. This kind of visibility-matching operator was described in [20], and we show the result in Fig. 4.…”

Section: Gamut Mappingmentioning

confidence: 99%

High Dynamic Range Imaging

2006

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The ultimate in color reproduction is a display that can produce arbitrary spectral content over a 300-800 nm range with 1 arc-minute resolution in a full spherical hologram. Although such displays will not be available until next year, we already have the means to calculate this information using physically-based rendering. We would therefore like to know: how may we represent the results of our calculation in a device-independent way, and how do we map this information onto the displays we currently own? In this paper, we give an example of how to calculate full spectral radiance at a point and convert it to a reasonably correct display color. We contrast this with the way computer graphics is usually done, and show where reproduction errors creep in. We then go on to explain reasonable short-cuts that save time and storage space without sacrificing accuracy, such as illuminant discounting and human gamut color encodings. Finally, we demonstrate a simple and efficient tone-mapping technique that matches display visibility to the original scene.

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“…Fig. 6a is obtained through Ward's operator (Ward Larson et al, 1997) which is known to maximize the contrast. Fig.…”

Section: Tone Mappingmentioning

confidence: 99%

Blind Contrast Enhancement Assessment by Gradient Ratioing at Visible Edges

Hautiére¹,

Tarel²,

Didier³

et al. 2011

Image Anal Stereol

673

332

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The contrast of outdoor images acquired under adverse weather conditions, especially foggy weather, is altered by the scattering of daylight by atmospheric particles. As a consequence, different methods have been designed to restore the contrast of these images. However, there is a lack of methodology to assess the performances of the methods or to rate them. Unlike image quality assessment or image restoration areas, there is no easy way to have a reference image, which makes the problem not straightforward to solve. In this paper, an approach is proposed which consists in computing the ratio between the gradient of the visible edges between the image before and after contrast restoration. In this way, an indicator of visibility enhancement is provided based on the concept of visibility level, commonly used in lighting engineering. Finally, the methodology is applied to contrast enhancement assessment and to the comparison of tone-mapping operators.

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A visibility matching tone reproduction operator for high dynamic range scenes

Cited by 620 publications

References 20 publications

Real-Time High-Dynamic Range Texture Mapping

Real-Time High-Dynamic Range Texture Mapping

High Dynamic Range Imaging

Blind Contrast Enhancement Assessment by Gradient Ratioing at Visible Edges

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