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Computer Science Department – Polytechnic Institute of Leiria, 2012

Contents

iii

Contents

1. HIGH DYNAMIC RANGE ..............................................................................................................9 1.1 1.2 1.3 1.4 RGB.........................................................................................................................................9 PRODUCE ................................................................................................................................11 STORING .................................................................................................................................13 VISUALIZING............................................................................................................................14

2. BIBLIOGRAPHY .........................................................................................................................17

List of Figures

v

List of Figures

Figure 1 – Dynamic Range acquired by the HVS. .......................................................................................... 9 Figure 2 – Electromagnetic spectrum........................................................................................................... 10 Figure 3 – RGB constraint in a CIE chromaticity diagram [Walker '96]. ...................................................... 10 Figure 4 – Left: In the 1590 painting “La Agoria en el Jardin”, El Greco used saturated colours of opposing hues to increase the apparent dynamic range of the scene.Right: Photograph taken around 1915 by Prokudin Gorskii. He managed to extend the dynamic range by using black-and-white film together with colour filters [Meyer '04]. .................................................................................................................... 11 Figure 5 – HDR image obtained from several photographs taken under different exposure times [Urbano, et al.'08].................................................................................................................................................. 12 Figure 6 – Image rendered with Radiance (© Carsten Bauer) [Radforum]. .................................................. 13 Figure 7 – A demo between a commercial high definition TV and Brightside’s equipment in a black room. Both are on in full black,side by side. The Brightside’s display is on the right of the image [Richards '05]. ..................................................................................................................................................... 15

List of Tables

vii

List of Tables

Table 1 – HDR file formats......................................................................................................................... 14

High Dynamic Range

9

1. High Dynamic Range
The human eye can process an almost unlimited amount of information. The efficiency is such that it can detect a single photon and work perfectly in extreme lighting conditions. For example, a sunny day can present values higher than 105 cd/m2 and a starlit night values around 10-3 cd/m2 [Wandell '95]. TheHVS has the capacity to easily adapt itself to everyday scenarios. Instantaneously it can capture contrasts of 10000:1 and distinguish in a particular frequency about 10000 different colours [Ward '98a]. With visual adaptation it can achieve values of 14 orders of magnitude (Figure 1).

Figure 1 – Dynamic Range acquired by the HVS.

It is precisely this relation between these maximum andminimum values that defines dynamic range, and it is this enormous range perceived by the HVS that is called High Dynamic Range (HDR).

1.1 RGB
The ‘true colour’ RGB colour model has the ability to combine several million colours. Some may think that this enormous quantity is perfectly suited to digitally represent the whole electromagnetic spectrum visible by the HVS (Figure 2). That is not...
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