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F. Zaraga and G. Langfelder Vol. 27, No. 1 /January 2010 /J. Opt. Soc. Am. A 31

White balance by tunable spectral responsivities

Federico Zaraga and Giacomo Langfelder*

Electronics and Information Department, Politecnico di Milano, via Ponzio 34/5, I-20133 Milano, Italy*Corresponding author: [email protected]

Received October 16, 2009; accepted October 28, 2009;posted November 10, 2009 (Doc. ID 118637); published December 3, 2009

The development of color pixels in modern digital imaging has led to devices in which color detection is notbased on the use of physical color filters but relies on the wavelength dependence of the silicon absorptioncoefficient in the visible range. In some of these devices the responsivity of each color channel can be electri-cally tuned by changing the applied voltages. Exploiting this feature, this paper presents a new method ofwhite balance that compensates for changes in the illuminant spectrum by changing accordingly the spectralresponsivities, and therefore the native color space, of the detector. Different sets of responsivities correspond-ing to the different RGB color channels can be selected, depending on the illuminant, in order to keep thechromatic components of a white object independent of the illuminant. An implementation of this method withthe transverse field detector, a color device with tunable spectral responsivities, is discussed. Experimentaldata show that the method is effective for three spectral sources that are strongly different from a chosen ref-erence source. The color error in a perceptive color space after the subsequent color correction (specific for eachset of base filters) does not change significantly in the tuning interval of interest for image acquisition.© 2009 Optical Society of America

OCIS codes: 100.2000, 110.1085, 110.2970.

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. INTRODUCTIONhe spectrum of the radiation diffused by an object is a

unction of the object spectral reflectance and of the illu-inant spectrum. Therefore the color of an object changesith the illuminant [1]. The photoreceptive sensitivity of

he human visual system is somehow able to compensateor the changes in the illuminant by a mechanism knowns chromatic adaptation. In particular a white object istill perceived white when changing the illuminant. Thishenomenon is called color constancy and has been widelytudied for many years [2,3].

Photographic devices simply record the spectrum of theight diffused by an object as transmitted through a lim-ted number of color filters, usually three or four. The re-ult of this undersampling is definitely dependent on thelluminant, and the resulting image has colors whicheem not faithful when observed under different condi-ions. The image recorded appears to have a “cast,” whichs considered unacceptable for image quality and must beorrected. The usual compensation procedure consists of aorrection of the colors, once acquired, in such a way thathe color coordinates of an achromatic object becomehose expected under a reference illuminant. The proce-ure is therefore usually indicated as white balance (WB).he residual errors in other colors are partially fixed in aubsequent step of color correction (usually performed lin-arly through a color correction matrix [4]).

Any WB algorithm obviously needs some informationbout the illuminant spectrum, which can be eithernown before the image acquisition, or calculated fromhe image itself with various algorithms [5–7], or mea-ured by an auxiliary sensor. In the present work the il-uminant is assumed to be known a priori and only theonsequent WB operation is discussed.

Several methods for WB have been proposed, some of

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hich are quite sophisticated, likely more close to the hu-an eye vision mechanism, and based for instance on the

ameson and Hurvich theory of induced opponent re-ponse [8]. The operation usually performed in digital im-ging photographic equipment is simply a linear correc-ion that independently adjusts each color channel,sually based on the diagonal von Kries coefficient law4,9–11]. Other techniques based on non-von-Kries (orondiagonal) color prediction or on spectral functionharpening have been proposed [12,13]. Nevertheless allhese techniques, as well as the more common von Kriesorrection, operate on the pixel color values after the im-ge has been acquired.In the present work a new WB method is discussed: theethod consists of tuning the spectral responsivities

TSR) of the various color channels of the digital photo-raphic apparatus in order to compensate for the illumi-ant change. The responsivities are adjusted in such aay that the ratio of photons detected by each color chan-el for a white object do not change when changing the

lluminant. With a conventional sensor, this could bemplemented by adding a suitable correlated color tem-erature (CCT) filter in front of the image acquisition ap-aratus. Each color channel has an overall transmittancehat is modified by the CCT filter transmittance. This op-ration has the obvious drawback of reducing the system’suantum efficiency [14].New strategies for the implementation of color pixels inodern digital imaging have led to devices in which color

etection is not based on the use of physical color filters15–18] and in which the channels’ responsivity can belectrically tuned [19]. For these devices the TSR-WB cane implemented without affecting the pixel quantum effi-iency.

With respect to Von Kries WB algorithms and to WB al-

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32 J. Opt. Soc. Am. A/Vol. 27, No. 1 /January 2010 F. Zaraga and G. Langfelder

orithms involving the use of external CCT filters, theSR-WB is expected to improve the signal-to-noise ratio

SNR), as will be detailed in the following.The paper is organized as follows. In Section 2 two ex-

mples of tunable sensors are presented, focusing on theransverse field detector (TFD), the one experimentallysed in this work. In Section 3 the TSR-WB is described,eferring to a generic photographic apparatus. Section 4eports the theoretical background showing the advan-ages of the TSR-WB in terms of SNR. Finally Section 5hows that, starting from a reference D65 source, theFD can effectively compensate changes of the illuminantsing the TSR-WB. The other considered illuminants arehe standard A, the standard D75, and a fluorescentource.

. TUNABLE SENSORSsensor of a photographic apparatus samples the spatial

istribution of the intensity of the scene and converts theptical signal into electrical signals. It also acquires alsonformation on the spectral distribution of the incomingadiation, usually by means of a limited number of differ-nt color filters that form an array in front of the pixelatrix (CFA) [20,21]. Each CFA may have a different pat-

ern or different spectral transmittances of the filters,hich can result in a better color rendition under certain

lluminants. However, once the filter combination is cho-en there is no way to change the native color space of thehotodevice.A different approach to color detection for digital imag-

ng devices has been proposed by Gilblom et al. [15,16]. Inheir device, three stacked PN junctions drawn at a suit-ble depth absorb photons mostly belonging to differentegions of the visible spectrum, as the absorption coeffi-ient of silicon changes with wavelength. The spectralhotoresponses of the junctions built at different depthsre thus different. Figure 1(a) depicts a schematic crossection of the structure [15]: the three junctions are rep-esented by solid lines, and their collection regions extendpproximately over distances db, dg, and dr. The fron-iers of each collection region may be shifted up or downy changing the junctions’ reverse biasing potential. As aonsequence the collection regions’ db, dg, and dr woulde modified. The spectral responses might thus be tun-ble provided that the extension of the junctions’ deple-ion region can be adjusted in a significant way, which re-uires a careful selection of the different doping levelsnvolved in the three stacked junctions’ design.

A similar approach to color detection is that of theransverse field detector (TFD), a silicon CMOS pixel de-ector for color imaging without CFA recently proposed byhe authors [17,18,22]. In this work the TFD has beensed as a TSR device to adjust the spectral responsivities.olor detection is performed by exploiting the dependencyf the silicon absorption coefficient on the wavelength inhe visible range, as in the Foveon solution [15]. However,here is a sole depleted region extending �3 to 5 �m inhe silicon depth. In a large part of this region, carriersbsorbed at a different depth (and thus mostly generatedy different wavelengths) are driven to different surfacelectrodes by means of a suitable electric field configura-

ion obtained in the depleted region, generated by theame biasing/collecting electrodes. Figure 1(b) is a sche-atic cross section of the device in which the isopotential

ines are shown, together with three different solid ar-ows representing the collection trajectories for carriersenerated at different depths. This electric field configu-ation, obtained by means of the voltages applied to con-acts Vb, Vg, and Vr, can be modified through a differentiasing of these electrodes. In this way the carriers’ col-ection trajectories are changed and thus the spectral re-ponses can be tuned. A detailed description of responsiv-ty tuning in the TFD is given in [19].

In the TFD a single depleted region is shared by the bi-sing contacts in different ways depending on the differ-nt set of applied reverse voltages. The spectral photore-ponses can be arranged in different shapes by changinghe way the collecting contacts share the depletion region,.e., simply by changing the biasing values. This change inhe biasing does not change the overall quantum effi-iency as it only redistributes to the electrodes in a differ-nt way the same number of photoelectrons.

The responsivity tuning obtainable with the TFD isarge enough to compensate the change of the illuminanthrough a TSR-WB technique: in Section 5 the experi-ental results will show that, with respect to a reference

ig. 1. Examples of color pixels with tunable spectral responses:a) A 3-color device built through stacked junctions [14,15]. Thehotoresponse of the nth junction may be varied by changing thextent of its depleted region dn. (b) Isopotential lines in the activeayer of the TFD [16–18]. This device has a sole depleted region.n a large part of this region a suitable electric field configurationrives carriers generated at different depths to different surfacelectrodes. In the scheme the arrows represent the trajectories ofhree carriers generated at different depths. A different electriceld configuration can lead to different collection trajectories.

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65 illuminant, the compensation can be done for severallluminants typically encountered in everyday life photog-aphy.

. NEW WHITE BALANCE ALGORITHMhe image acquisition apparatus for purposes of theresent discussion can be divided into three sections, ashown in Fig. 2:

1. An optical section, in which the information abouthe scene is represented by space- and wavelength-ependent electromagnetic waves. This section usuallyomprises a lens, a diaphragm, a low-pass filter, IR and eV blocking filters, a microlens array, and often a me-

hanical shutter.2. An electrical analog section, where the electromag-

etic signal has been sampled for the space dependencein different pixels), but each signal amplitude is still rep-esented and processed as an analog value of charge oroltage.

3. A digital section, where the amplitude of each signalas been digitized and all the information is representedy a set of numbers.

n this schematic representation the sensor is the inter-ace between section 1 and 2, and one or more A/D con-erters constitute the interface between the analog andhe digital section.

The WB correction is usually performed in the finaligital section 3, together with all the other image elabo-ations: demosaicing, color correction, gamma correction,oise reduction, sharpening, etc. The correction can beerformed in the native RGB space, usually following theon Kries approach, by means of a diagonal matrix, wherehe matrix elements are the ratios between RGB signalsorresponding to the image of an achromatic color withhe picture illuminant and with the reference illuminant.

similar correction based on the same coefficients can beerformed in the analog section by means of adjustableain amplifiers specific for each color channel, with somedvantages in terms of image quality because of a better

ig. 2. Simplified scheme of a photographic apparatus for digiigital section. In the present work it is instead performed by m

atch of the signal dynamics with the A/D converter in-ut, and possibly a better SNR.All these correction techniques are applied when the

ignal has already been detected by the sensor: they ba-ically amplify the signal in those spectral portions wherehe illuminant is less intense with respect to the referencelluminant: for instance the blue portion of the spectrumor an A CIE standard lamp [tungsten with 2856 K corre-ated color temperature (CCT)] with respect to a CIE D65daylight with 6500 K CCT) reference illuminant, as de-icted in Fig. 3. The blue channel in this situation has amall signal and therefore a lower SNR. The equalizationade by this amplification, either analog or digital, am-

lifies the noise of the channel with a weak signal; subse-uent operations with algorithms involving adjacent pix-ls may spread this noise. The SNR of the whole image ishus lowered.

In this paper a new approach to WB is discussed: theethod consists of the tuning of the TSR of the detector,hich are the characteristics of the interface between theptical and the analog electrical section (1 and 2 in Fig. 2),n order to adapt them to the spectra of the illuminants23].

With this method, for each CCT of the illuminant, apecific set of base RGB responsivities is used, tuning theative chromatic color space of the sensor. The new nativeolor space is such that the achromatic color with the spe-ific illuminant is always represented by a vector withqual components on each axis. This means that the ref-rence color system is adapted to the white signal and notice versa. In Section 4 it will be shown that this leads tohe obvious advantage that no analog/digital amplifica-ion is required, and there is no consequent noise multi-lication.

. THEORETICAL BACKGROUNDn this section the advantages of the TSR-WB with re-pect to traditional WB methods in terms of SNR are dis-ussed. We consider that the photocurrent generated byn incident radiation is integrated over a capacitance C

aging: the white balance is usually performed in the analog orf a tuning of the sensor responsivities (TSR) inside the sensor.

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or an integration time tint, a common situation both forctive and for passive pixel sensors. The calculation of theNR is based on the pixel noise model described in [24].The equivalent filter spectral transmittance of the nth

ontact of a photodiode is defined as the ratio between thehotocurrent measured at this electrode at every wave-ength and the total photocurrent that would be mea-ured at the same wavelength on a white pixel (i.e., witho filter and with no transverse electric field) [19]. Thisefinition is exploited here for a straightforward compari-on between sensors with or without physical color filters.detailed description of the apparatus and the procedure

or the measurements of the equivalent filter spectralransmittances can be found in [19].

The spectral power density of a generic scene can beepresented as the product of the illuminant spectralower density L�� by the reflectance of the scene r��.he detecting device is characterized by a responsivity��. On top of the traditional device is generally inter-osed a set of n color filters, each with a transmittance

n��. In this situation, the current representing the sig-al in the photodevice can be written as

in =��min

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vn = intint/C. �2�

n this situation the noise is generated both inside theixel (as a shot noise contribution of the signal and darkurrent) and outside the pixel during the readout opera-ion (input referred amplifier noise, reset noise, fixed pat-

ig. 3. Spectral radiance of four common but strongly differentources: the standard D65, simulating the daylight on a sunnyay (solid curve); the standard A, simulating a tungsten bulb at856 K (dotted curve); the standard D75, simulating a daylightt northern latitudes (dashed curve); a fluorescent lampdashed–dotted curve). All the radiances are taken from the ISEToftware and are cut off at the ends of the visible spectrum byeans of a UV and an IR filter.

ern noise). The overall voltage noise at the pixel output isiven by [24]

�n = �2q�in + id�tint + �fixed2 /C, �3�

here id represents the pixel dark current and the seconderm inside the square root represents all the noise con-ributions listed above, assumed to be zero mean and toave average spectral power �fixed

2 .In the context of the present work, a sensor with three

olor filters (or equivalent color filters) and analog/digitalains natively set to balance a perfect diffuser illumi-ated by a D65 reference source is considered. The sensor

s then used to record the image generated by a standardilluminant reflected by a perfectly white diffuser. It is

hus assumed r��=1 and L��=LA��. As the illuminants strongly higher in the red portion of the spectrum withespect to the blue spectral region (Fig. 3), the three pix-ls’ output signals are significantly different:

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traditional WB method applies gains in the analog origital section of the apparatus so that

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his operation also multiplies the noise terms by theame gain factors; as a consequence, the SNR of the bluehannel is not increased and remains

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s previously mentioned, the SNR of the blue channel,hich in this situation is the lowest, ordinarily can be

pread to the other color channels during operations in-olving adjacent pixels. The SNR of the whole image ishus lowered.

In a sensor with TSR, on the other hand, the TSR-WBethod can be applied in order to equalize the three chan-els’ signals prior to the integration by a tuning of theequivalent) color filters:

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nd is thus higher with respect to the previous situation,s in Eq. (9) ib� is higher with respect to ib in Eq. (7).From a simplified geometrical point of view, the tradi-

ional WB method corresponds to a change of the direc-ion of the vector representing the color of a perfect dif-user (white) taken with any illuminant in order to alignt with the direction of the same diffuser taken with theeference illuminant (e.g., the D65).

ig. 4. (Color online) Experimental spectral sensitivities of theurves show the filters tuned for the D65 source, the dotted curource, and the dashed–dotted lines those for the fluorescent lamtep of deposition on top of the detector of several protective layeor the jagged behavior of the spectral responsivity curves.

Here, however, when the illuminant is varied the pro-osed TSR-WB accordingly changes the chromatic refer-nce system. The new set of base RGB responsivities iselected in order to have the color of the perfect diffuserith the new illuminant represented by vectors that havequal components on the axis of the new color space. In-tead of moving the vectors, the reference system is ad-usted.

. EXPERIMENTAL RESULTShe spectral responses of the TFD detector with variousias potentials were measured by means of a light sourcef known spectral intensity and a monochromator. Thepectral sensitivities have been obtained by measuringhe photocurrents generated by a variable wavelengthonochromatic radiation in the visible range.

. Characterization under the Reference D65 Sourcehe solid curves in Fig. 4 show the spectral sensitivities ofhe RGB color channels obtained with biasing potentialsB=1.25 V, VG=3.40 V, VR=3.75 V. The signals are then

ndependently amplified with fixed gains in the analog

GB electrodes [(a), (b), (c), respectively] used in this work. Solidse tuned for the A source, the dashed curves those for the D75particular CMOS process used in this work has an unavoidable

ich do not transmit evenly the incoming light. This is the reason

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ection. After this operation the three integrals of Eq. (1)ave the same values for an illuminant D65 CIE stan-ard. This means the sensor is initially balanced in nativeGB space (normalized to unity) for the reference illumi-ant, as the signals measured from an achromatic colorre the same for the three color channels: iR=0.333, iG0.333, iB=0.333.There are various combinations of tunable filter sensi-

ivities that can balance the three integrals. The onehown is chosen as it gives a reasonably small error in theubsequent color conversion operation, as will be seenater in this section.

It is well known that the transformation to a standardolor space as CIE XYZ by means of a linear transforma-ion cannot be accurate for all colors, unless the imagingpparatus satisfies the Luther conditions (that is, spec-ral sensitivities are linear transformations of the coloratching functions [25]). Errors in this color rendering

ransformation can arise from sensor spectral responsivi-ies not consistent with those of the human eye. These er-ors can be summarized by the differences between theriginal and the measured colors in a perceptual colorpace (Lab). Errors for the TFD sensor with the previ-usly reported bias potentials have been evaluated for thepectral sensitivities generated with the tuning processnd turn out to be of the same order of those reported foronventional nontunable sensors.

A color correction matrix (CCM) has been calculated byeans of the least-squares method, using as a set of ref-

rence colors those of the Gretag Macbeth Color CheckerMCC) illuminated by the reference source CIE D65. Therocess of acquiring the MCC colors was simulated byeans of the ISET software [26,27], using as spectral sen-

itivities those measured as discussed above. The ISEToftware simulates a scene and an imaging optics to con-entrate the light on a simulated silicon pixel sensor andalculates the number of collected electrons at each con-act. For each of the 24 patches of the MCC, three differ-nt voltage values are obtained (one per contact), whichonstitute the color coordinates in the particular TFDolor space. These values are then converted to the nor-alized CIE 1931 xy space by means of a CCM calculated

y the simulator with a least-squares method.The CCM M1 for the filters represented by the solid

urves in Fig. 4 turns out to be

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igure 5 shows the original and calculated colors in the xypace for the MCC. The correspondent chromaticity aver-ge error in the perceptual Lab space is �Eab=3.4. Theorrection moves the white point from the ideal positiono the one represented by the circle markers in Figs.(a)–6(c).

. TSR-WB To Compensate the A Illuminantsecond situation with the MCC illuminated by a CIE A

tandard source has been simulated with the ISET soft-are. The A illuminant, corresponding to a tungsten

amp, has a spectrum quite different from that of the D65,

s shown in Fig. 3. Its relative intensity of the blue por-ion referred to the red portion of the spectrum is smallerhan in the D65, and has thus been chosen as the exampleor this discussion because the switch between the twoources is a good test for sensitivity tuning.

The signals measured from an achromatic color with-ut any change from the previously adopted D65 settingsre now obviously unbalanced and the values for thehree color channels are iB=0.25, iG=0.34, iR=0.41. Theseignal values, using the CCM M1 previously calculated forhe first set of spectral sensitivities, correspond to the xyoordinates close to those of a black body with a CCT of856 °K as shown in Fig. 6 by the x marker.To perform the WB by the method discussed in this pa-

er the color space is adjusted in order to have the vectorepresentative of the color of an achromatic object withhree equal components. Bias voltages have been changedo a new set of values: VB=3.70 V, VG=2.25 V, VR2.10 V. The corresponding spectral sensitivities are rep-esented by the dotted curves of Fig. 4. The new, tuned,esponsivities are higher in the spectral regions wherehe illuminant is weaker, and the values of the signalseasured with the ISET software for the three channel

eturn to B=0.333, G=0.331, R=0.336, quite close to thedeal white point. These values, corrected by the CCM M1orrespond to the square markers in Fig. 6(a). This repre-entation is used only to highlight the effect of the WB op-ration, which effectively brings the white point close tohe desired value. Obviously the new set of spectral sen-itivities requires a new color conversion matrix. A newCM M2 has thus been calculated in order to represent

he measured colors in the xy space. The position of thehite point with the A illuminant after the correction of

he color points with M , is shown in Fig. 6(a) (plus sign).

ig. 5. xy representation of the colors of a Gretag Macbethhecker illuminated by a D65 source as measured by the TFDith spectral sensitivities equal to the solid curves of Fig. 4

ransformed with the CCM M1 (circles). The error bars lead tohe original color points.

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t is practically coincident with the white correspondingo the D65 light source (circle marker).

The correspondent chromaticity average error in theerceptual Lab space after the correction through theCC M2, is �Eab=3.1. The error is close to that of the

revious set of spectral sensitivities tuned for the D65.

. TSR-WB to Compensate the D75 Illuminantn a third situation a simulation of the MCC illuminatedy a standard CIE D75 source has been performed. Withespect to the CIE D65 source this illuminant is bluish,nd thus the white point shift in the color space (when no

ig. 6. Points representing the color of a perfect diffuser obtainellumination through the D65 source and to the spectral sensitivhe color conversion through M1. The x marker refers to the samethe A source in (a), the D75 source in (b), and the fluorescentSR-WB algorithm. The final points after the new color correctio

B is applied) is in the opposite direction with respect tohe former case of the A illuminant.

All the operations previously described for the compen-ation of the A illuminant were repeated: the tuning wasbtained in this case by setting the three voltage values toB=0.90 V, VG=3.10 V, VR=3.70 V. Comparing this tun-

ng with the tuning performed for the A illuminant, it cane noted that the spectral sensitivity of the blue channels now decreased, while that of the red channel is in-reased. These values give the spectral responsivities rep-esented by the dashed curves in Fig. 4. The positions ofhe white point before the TSR-WB, after the TSR-WB,

e different situations described in the box. The circles refer to anned for the D65 source (depicted by solid curves in Fig. 4) aftervities set, but to an illumination obtained from a different sourcein (c)]. The square quantitatively represents the effect of the

ugh a new, suitable CCM are represented by the plus sign.

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nd after a final correction of the other colors through auitable CCM M3 are shown in Fig. 6(b) by the x marker,he square, and the plus sign, respectively. The final chro-aticity average error in the perceptual Lab space after

he correction through the MCC M3, is �Eab=3.6.

. TSR-WB to Compensate a Fluorescent Illuminantinally, in a fourth situation a simulation of the MCC il-

uminated by a fluorescent illuminant whose spectrum ishown in Fig. 3 (embedded in the ISET software) was per-ormed. With respect to all the other considered sources, auorescent lamp is characterized by a notched spectrumith high emission peaks. It therefore represents anotherifferent type of spectral variation with respect to the cho-en reference illuminant, and thus another particularondition to test the potential of the TSR-WB.

All the operations previously performed for the com-ensation of the other illuminants were repeated: the tun-ng was obtained in this case by setting the three voltagealues to VB=1.70 V, VG=3.40 V, VR=3.60 V. These val-es result in the spectral responsivities represented byhe dashed–dotted curves in Fig. 4. The position of thehite point before the TSR-WB, after the TSR-WB, andfter a final correction of the other colors through a suit-ble CCM M4 is shown in Fig. 6(c) by the x marker, thequare, and the plus sign, respectively. The final chroma-icity average error in the perceptual Lab space after theorrection through the MCC M4, is �Eab=3.7.

All our results are summarized in Table 1. As the newroposed method for WB gives good results with the fourtrongly different sources used as examples in this work,t is expected it would give good results for any lightource with a white point in an intermediate position be-ween the ones here analyzed, provided that for eachource a specific CCM is precalculated and, for instance,tored in a look up table (LUT) of the photographic equip-ent. The LUT associates with every spectral source a set

f biasing values, implementing the adapted chromaticpace through the tuning of the TSR sensor photospectralunctions.

. CONCLUSIONSnew method to perform the white balance in a digital

hotographic apparatus has been presented. This methods unique with respect to any other WB technique in thatt adjusts the color space of the sensor, adapting it to thenown illuminant prior to image acquisition. The colorpace is adjusted through the tuning of the native RGBesponsivity functions of the sensor. In this work theethod has been successfully applied using the TFD, a

olor sensitive device with electrically tunable responsivi-

Table 1. Summary of the Experimental Results

Source V1 [V] V2 [V] V3 [V] �Eab,2000

D65 1.25 3.40 3.75 3.4A 3.70 2.25 2.10 3.1

D75 0.90 3.10 3.70 3.6Fluo. 1.70 3.40 3.60 3.7

ies, but can theoretically be applied to any sensor inhich the native color space is programmable. Within the

heoretical advantages of the proposed method is a re-uced worsening of the SNR after the white balance. Onhese lines a detailed comparison between the perfor-ance of the proposed method and other common WB al-

orithms will be the object of future work.

EFERENCES1. B. A. Wandell and L. D. Silverstein, “Digital color

reproduction,” in The Science of Color (Elsevier, 2003), pp.281–316.

2. D. L. MacAdam, “Chromatic adaptation,” J. Opt. Soc. Am.46, 500–513 (1956).

3. B. A. Wandell, “Color appearance and the digital imagingpipeline,” in Proceedings of the 15th InternationalConference on Pattern Recognition (ICPR, 2000), Vol. 1, pp.183–190.

4. G. D. Finlayson, M. S. Drew, and B. V. Funt, “Colorconstancy: generalized diagonal transforms suffice,” J. Opt.Soc. Am. A 11, 3011–3019 (1994).

5. S. Bianco, F. Gasparini, and R. Schettini, “Combiningstrategies for automatic white estimation in real images,”in Proceedings of 14th International Conference on ImageAnalysis and Processing Workshops (ICIAPW, 2007), pp.175–178.

6. F. Gasparini and R. Schettini, “Color balancing of digitalphotos using simple image statistics,” Pattern Recogn. 37,1201–1217 (2004).

7. C. Weng, H. Chen, and C. Fuh, “A novel automatic whitebalance method for digital still cameras,” in Proceedings ofIEEE International Symposium on Circuits and Systems(ISCAS) (IEEE, 2005), pp. 3801–3804.

8. K. Hirakawa and T. W. Parks, “Chromatic adaptation andwhite-balance problem,” in Proceedings of the InternationalConference on Image Processing (ICIP, 2005), pp. 984–987.

9. G. Wyszecki and W. S. Stiles, Color Science: Concepts andMethods, Quantitative Data and Formulae, 2nd ed. (Wiley,1982).

0. S. Quan, “Evaluation and optimal design of spectralsensitivities for digital color imaging,” Ph.D. thesis(Rochester Institute of Technology, 2002).

1. H. Y. Chong, S. J. Gortler, and T. Zickler, “The von Krieshypothesis and a basis for color constancy,” in Proceedingsof the IEEE International Conference on Computer Vision(IEEE, 2007), pp. 1–8.

2. B. Funt and H. Jiang, “Non-von-Kries 3 parameter colorprediction,” Proc. SPIE 5007, 182–189 (2003).

3. G. D. Finlayson, M. Drew, and B. Funt, “Spectralsharpening: sensor transformations for improved colorconstancy,” J. Opt. Soc. Am. A 11, 1553–1563 (1994).

4. H. P. Gage, “Color filters for altering color temperature.Pyrometer absorption and Daylite glasses,” J. Opt. Soc.Am. 23, 46–54 (1933).

5. R. B. Merrill (Foveon Inc.), “Color separation in an activepixel cell imaging array using a triple-well structure,” U.S.Patent 5,965,875, October 12, 1999.

6. D. L. Gilblom, S. K. Yoo, and P. Ventura, “Real-time colorimaging with a CMOS sensor having stacked photodiodes,”Proc. SPIE 5210, 105–115 (2004).

7. A. Longoni, F. Zaraga, and G. Langfelder, “Luminousradiation color photosensitive structure,” Italian PatentMI2006A002352 (2006); International Patent Appl. PCT/IB2007/003906.

8. A. Longoni, F. Zaraga, G. Langfelder, and L. Bombelli, “Thetransverse field detector: a novel color sensitive CMOSDevice,” IEEE Electron Device Lett. 29, 1306–1308 (2008).

9. G. Langfelder, F. Zaraga, and A. Longoni, “Tunable spectralresponses in a color sensitive CMOS pixel for imagingapplications,” IEEE Trans. Electron Devices 56, 2563–2569(2009).

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2

2

2

2

2

2

2


0. B. E. Bayer, “Color imaging array,” U.S. Patent 3,971,065,July 20, 1976.

1. A. El Gamal and H. Eltoukhy, “CMOS image sensors,”IEEE Circuits Devices Mag. May–June, pp. 6–20, 2005.

2. G. Langfelder, “Isolation of highly doped junctions in low-doped active layers for CMOS radiation detectors,” IEEETrans. Electron Devices 56, 1767–1773 (2009).

3. F. Zaraga and G. Langfelder, “Foto-rivelatore e metodo perrivelare una radiazione ottica,” Italian PatentMI2009A000500 (2009).

4. D. X. D. Yang and A. El Gamal, “Comparative analysis of

SNR for image sensors with enhanced dynamic range,”Proc. SPIE 3649, 197–211 (1999).

5. P. L. Vora and H. J. Trussel, “Measure of goodness of a setof color-scanning filters,” J. Opt. Soc. Am. A 10, 1499–1508(1993).

6. Image System Evaluation Toolbox—ISET 2.0 User Manual,ImagEval Consulting.

7. J. E. Farrell, F. Xiao, P. B. Catrysse, and B. A. Wandell, “Asimulation tool for evaluating digital camera image quality,image quality and system performance,” Proc. SPIE 5294,
124–131 (2004).

white balance by tunable spectral responsivities

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