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Evaluation of High Dynamic Range Photography As a Luminance Data Acquisition System

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Evaluation of High Dynamic Range Photography As a Luminance Data Acquisition System Lighting Res. Technol. 38,2 (2006) pp. 123Á/136 Evaluation of high dynamic range photography as a luminance data acquisition system MN Inanici PhD Lawrence Berkeley National Laboratory, Lighting Research Group, Berkeley, California, USA Received 17 January 2005; revised 21 July 2005; accepted 9 August 2005 In this paper, the potential, limitations and applicability of the High Dynamic Range (HDR) photography technique are evaluated as a luminance mapping tool. Multiple exposure photographs of static scenes were taken with a commercially available digital camera to capture the wide luminance variation within the scenes. The camera response function was computationally derived by using Photosphere software, and was used to fuse the multiple photographs into an HDR image. The vignetting effects and point spread function of the camera and lens system were determined. Laboratory and field studies showed that the pixel values in the HDR photographs correspond to the physical quantity of luminance with reasonable precision and repeatability. 1. Introduction lengthy and complex physical measurements performed in laboratory conditions, accompa- nied with extended data analysis.1,2 RGB It possible to measure the photometric proper- values were converted to the CIE tristimulus ties of a scene by means of point-by-point values through the calibration functions. measuring devices. However, these measure- These early studies were based on single ments take a long time, are prone to errors due photographs, which provide a limited dynamic to measurement uncertainties in the field and range of luminances. More recent techniques3 the obtained data may be too coarse for employ multiple photographs, which allow a analysing the lighting distribution and varia- larger luminance range to be captured. Some tion. There is a need for a tool that can of these techniques require expensive equip- capture the luminances within a large field of ment. All of these studies require costly and view at a high resolution, in a quick and tedious calibration processes, and yield cali- inexpensive manner. bration functions that are strictly device Photography has the potential for this kind dependent. of data collection. Photograph based photo- metry is not a new approach; various research- In HDR photography, multiple exposure ers have utilized film based photographs and photographs are taken to capture the wide CCD outputs for luminance measurements. luminance variation within a scene. Camera The common approach in early studies was to response function is computationally derived acquire the calibration functions for a certain through a self-calibration process from the camera and illuminant, which involved multiple exposure photographs; therefore the HDR photography technique is applicable to Address for correspondence: MN Inanici is currently at: all cameras that have multiple exposure cap- University of Washington, Department of Architecture, Box abilities. The camera response function is used 355720, Seattle, WA 98195-5720, USA. E-mail: inanici@ w.washington.edu to fuse the photograph sequences into a single HDR image. HDR photography is not # The Chartered Institution of Building Services Engineers 2006 10.1191/1365782806li164oa 124 MN Inanici Table 1 Camera settings Feature Setting Feature Setting White balance Daylight Image size 2592 pixels/1944 pixels Best shot selector Off Sensitivity 100 ISO Image adjustment Normal Image sharpening Off Saturation control Normal Lens Fisheye Auto-bracketing Off Noise reduction Off specifically developed for lighting measure- held luminance meter with 1/38 field of view ment purposes. The objective of the present (Minolta LS110). study is to evaluate the appropriateness (ie, accuracy, applicability, and limitations) of the 2.2 Softwares technique as a luminance data acquisition The multiple exposure photographs were system. processed using the software called Photo- sphere.4 All photographs were taken with the camera settings shown in Table 1. It is 2. Equipment and softwares especially important to fix the white balance for achieving consistent colour space transi- 2.1 Equipments tions. Changing either the aperture size The multiple exposure photographs were (f-stop) or the shutter speed (exposure time) taken with a Nikon Coolpix 5400 digital can vary the exposure values. Shutter speed is camera mounted on a tripod and fitted with a more reliable measure than aperture size.5,6 a fisheye lens (Nikon FC-E9). The fisheye lens Therefore, exposure variations were achieved has a focal length of 5.6 mm and an angle of with a fixed aperture size (f/4.0), and varying view of 1908. Reference physical measure- only the shutter speed in manual exposure ments were taken with a calibrated hand mode (2 s to 1/4000 s). 1.0 Camera response curve Photosphere ) 2 0.8 m / d c ( e 0.6 c n a n i m u 0.4 L e n e c 0.2 S 0.0 0 1.0 Pixel/255 Figure 1 Camera response curve for Nikon 5400 as determined by Photosphere Lighting Res. Technol. 38,2 (2006) pp. 123Á/136 High dynamic range photography 125 An interior scene with daylight that had mented (referred to as HDRLab). The routines large and smooth gradients throughout the were written in Matlab† and they allow the interior and exterior views was selected for user to extract and process per-pixel lighting determining the camera’s natural response data from the HDR images saved in Radiance function.7 Photosphere generated the camera RGBE format. CIE XYZ values for each pixel response curve for the Nikon 5400 that was were quantified from floating point RGB used in this study based on 10 exposure values based on the standard colour space sequences in three channels (RGB) as follows (sRGB) reference primaries,10 CIE Standard (Figure 1): Illuminant D65, and standard CIE Colori- metric Observer with 28 field of view. The R1:53994x3 0:99492x2 0:46536x transformation process is performed as follows: 0:01037 1) Floating point RGB is calculated from 8 G 1:31795x3 0:69784x2 0:38994x RGBE integer values. 0:01005 R (E128) G (E128) 3 2 red +2 ; green +2 ; B1:67667x 1:09256x 0:42334x 255 255 0:00745 B The curves are polynomial functions blue +2(E128) that model the accumulated radiometric non- 255 linearities of the image acquisition process 2) CIE chromaticities for the reference pri- (such as gamma correction, A/D conversion, maries and CIE Standard Illuminant D65 image digitizer, various mappings) without are as follows:10 addressing the individual source of each non-linearity.5,6 The technique, known as R(x; y; z)(0:64; 0:33; 0:03) 5 radiometric self-calibration, is a computa- G(x; y; z)(0:30; 0:60:0:10) tionally derived calibration process used to relate the pixel values to the real world B(x; y; z)(0:15; 0:06; 0:79) luminances. Camera response curves vary D (x; y; z)(0:3127; 0:3290; 0:3583) considerably between different cameras, there- 65 fore radiometric self-calibration has to be 3) RGB to XYZ matrix is constructed with applied to each camera. However, the only the matrix of RGB chromaticities (‘K’), input to the process is a set of multiple which are differentially scaled to achieve exposure photographs. the unit white point balance (‘W’). Once the camera response curve is deter- Further information on RGB to XYZ mined, Photosphere can fuse any photograph conversion can be found in Wyszecki and sequence into a HDR image. HDR images can Stiles12 and Glassner.13 be stored in image formats such as Radiance 2 3 2 3 RGBE8 and LogLuv TIFF,9 where the pixel r r r 0:64 0:33 0:03 4 x y z 5 4 5 values can extend over the luminance span K gx gy gz 0:30 0:60 0:10 6 of the human visual system (from 10 to bx by bz 0:15 0:06 0:79 108 cd/m2). "# 2.3 Luminance calculation X Z W ¼ n 1 n ½0:9505 1:01:0891 For analysing the HDR images from Photo- Y Y sphere, computational procedures were imple- n n Lighting Res. Technol. 38,2 (2006) pp. 123Á/136 126 MN Inanici 25 100 Incandescent Average error percentages: 90 20 All: 7.9% 80 Grayscale targets: 4.6% ) Colored targets: 11.2% 70 2 m / d 15 60 ) c ( % ( e r c 50 o n r a r n E i 10 40 m u L 30 5 20 10 0 0 r a e e e e e e n y n n n n d 5 5 8 n 5 k d 1 9 7 5 0 1 3 8 6 2 2 4 w t t l i . , e i e e a u e w e g g c u e k i 1 1 1 l l o n l l p G G G G G G G G G k 3 6 k r r e s e e a a y o n l a a h w r s e s i r l r b l l r b G G G l l r r c a l e o l e u t t g t e g b g w g r a a t l k e o h r r u p u u a f h y a o r f t t l s y h e r e i w g a e u u b s m e l i e n n i o d l e e u g p l d l u l r n n n l o b e u a b y r p m o Greyscale and coloured targets Measured HDR error% Figure 2 Dark room with greyscale and coloured targets, illuminated with an incandescent lamp V ¼ WKÀ1 ¼ ½0:6444 1:1919 1:2032 applied as a constant (‘k’) either to the ÂÃ pixel values in an image or to the camera Gr Gg Gh response function.
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