Adaptive Contrast Adjustment for Postprocessing of Tone Mapped High Dynamic Range Images

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Aaptive Contrast Ajustent for Postprocessing of Tone Mappe High Dnaic Range Iages Manish Narwaria, Matthieu Perreira a Silva, Patrick Le Callet, Roual Pepion To cite this

IEEE International Sposiu on Circuits an Sstes (ISCAS) 2013, Ma 2013, Beijing, China. pp.1, 2013. <hal- 00825879> HAL I: hal-00825879 http://hal.univ-nantes.

not. The ocuents a coe fro teaching an research institutions in France or abroa, or fro public or private research centers.

1 Aaptive Contrast Ajustent for Postprocessing of Tone Mappe High Dnaic Range Iages Manish Narwaria, Matthieu Perreira a Silva, Patrick Le Callet, Roual Pepion To cite this version: Manish Narwaria, Matthieu Perreira a Silva, Patrick Le Callet, Roual Pepion. Aaptive Contrast Ajustent for Postprocessing of Tone Mappe High Dnaic Range Iages. IEEE International Sposiu on Circuits an Sstes (ISCAS) 2013, Ma 2013, Beijing, China. pp.1, <hal > HAL I: hal Subitte on 24 Ma 2013 HAL is a ulti-isciplinar open access archive for the eposit an isseination of scientific research ocuents, whether the are publishe or not. The ocuents a coe fro teaching an research institutions in France or abroa, or fro public or private research centers. L archive ouverte pluriisciplinaire HAL, est estinée au épôt et à la iffusion e ocuents scientifiques e niveau recherche, publiés ou non, éanant es établisseents enseigneent et e recherche français ou étrangers, es laboratoires publics ou privés.

2 Aaptive Contrast Ajustent for Postprocessing of Tone Mappe High Dnaic Range Iages Manish Narwaria, Matthieu Perreira Da Silva, Patrick Le Callet, Roual Pepion LUNAM Universit, IRCCN CNRS UMR 6597 Nantes, France, Abstract Tone apping operators (TMOs) eploe to visualize high naic range (HDR) content on conventional low naic range (LDR) evices suffer fro two ajor rawbacks. First, none of the can faithfull reprouce all the contrast present in HDR iages. Secon, ost of the require one or ore paraeters which are ostl content specific an their optial values can be set onl via subjective testing. To aress these issues, this paper proposes that qualit riven aaptive contrast enhanceent is a practical solution. This is achieve b enhancing the contrast aaptivel base on the loss of contrast between the HDR an tone appe iage. Eperiental results confir that the propose aaptive solution alwas iproves upon the contrast achieve fro whatever given TMO paraeter settings in the teste iages. So it helps to achieve the results of a ore optial TMO paraeter setting without the huan input. I. INTRODUCTION High Dnaic Range iaging (HDRI) has been steail gaining popularit in both acaeia an inustr [6]. The reason being that HDR faithfull epicts the naic range of the real worl luinance (tpicall varing fro 10-1 c/² to 10 5 c/²) b storing the as floating point values. As a result, an HDR iage can capture ver high contrasts which in turn enables it to incorporate aiu etails that the huan ee can iscern. However, the cost of HDR ispla technologies is currentl quite high an et to reach consuer levels. In such scenario, the onl alternative is to ispla HDR contents irectl on coonl available evices such as CRT, LCD onitors, printers etc. which have a significantl low naic range (LDR). It follows that these cannot provie the necessar luinance range (usuall their range lies between 1 to 300 c/²) for a true HDR eperience. Therefore an iportant issue in HDRI is to reuce the naic range of the HDR content. This proble has been coonl aresse b eploing tone apping operators (TMOs). Tone apping refers to the reuction in naic range so as to properl ispla the HDR content onto LDR evices. Several TMOs have been evelope over the past ears [6]. Soe are siple an base on operations such as linear scaling an clipping while the ore sophisticate ones eploit several properties of the Huan Visual Sste (HVS) [3] with the ai of preserving the iportant etails. Even though several TMOs eist, there are two ajor issues with the. First, ajorit (if not all) of the cannot preserve all the contrast present in the HDR iage. This can reuce the perceptual qualit of the tone appe contents ue to the introuction of artifacts relate to changes in contrast as well as loss of iportant etails. Secon, an TMOs involve one or ore paraeters which is usuall left for the user to set. Unfortunatel, there is no ssteatic an general etho to eterine the optial TMO paraeters. This issue is further coplicate b the fact that a set of TMO paraeters suitable for one iage content a not be optial for another. As a result, the best (an onl) wa to eterine paraeters values is through subjective tests which obviousl are not suitable for real-tie processing. II. PROPOSED IDEA To target the two aforeentione issues with eisting TMOs, we propose that the use of contrast enhanceent as a post processing step woul be beneficial in iproving the contrast of tone appe iages. This will particularl be effective in cases when the large aount of contrast has been aage as a result of TMO esign an/or the specifie TMO paraeters. Further it a also be entione that an TMOs operate locall as a result of which contrast loss occurs non-uniforl in ifferent iage regions (instea of a unifor contrast loss in the entire iage). Therefore, it is less effective to enhance the contrast of tone appe iages uniforl since soe regions a have lost ore etails as copare to others. That is, aaptive contrast enhanceent base on the loss of contrast is epecte to be a ore effective solution in restoring the contrast lost uring tone apping. To this en, we first assess the loss of contrast between the HDR iage an its corresponing tone appe iage. Net, we use this to eterine the clip liit for the contrast enhanceent algorith. The iea is that when ore contrast is lost in soe region, the clip liit is set to a higher value leaing to ore

3 HDR iag Tone apping LDR Loss of Contrast (graient) Clip liit Block base Contrast Enhanceent Algorith Enhance iage HDR No Final Enhance iage Yes Greater than threshol? Deterine Naturalness Figure 1. Block iagra of the propose aaptive post processing contrast enhanceent etho contrast enhanceent. Likewise, for regions where tone apping resulte in uch saller loss of contrast, the clip liit is autoaticall set to a lower value thereb liiting contrast enhanceent in that region. The final result is that the contrast of the tone appe iage is enhance aaptivel an in a ore qualit aware fashion rather than sipl appling contrast enhanceent to the whole iage. The final step in our etho is that of assessing the naturalness of the enhance iage. If the naturalness is grater than a threshol, then no further processing is require. If however, the naturalness is lower than the threshol, it iplies that the iage has probabl been over enhance aking it appear unnatural. Then corrective action is necessar b re-ajusting the clip liit. A block iagra of the propose etho is shown in Figure 1. Even though objective easureent of loss of contrast between HDR an tone appe iage an the naturalness are theselves challenging, we believe that our iea has potential an we have verifie it on a sufficientl large set of HDR iages processe b several well known TMOs. We foun that with the propose post processing the resultant iages usuall have better contrast an brightness. III. IMPLEMENTATION DETAILS In this paper, we aopte a graient base etho to assess the loss of contrast between the HDR iage an its corresponing tone appe version. We eploe the Sobel operator to copute the erivatives along the (row) an (colun) irections. We enote these as L (i, an L (i, at location (i, for the tone appe (LDR) iage. Siilarl for the HDR iage, we have H (i, an H (i,. We then easure the siilarit between the erivatives of the HDR an LDR iages to obtain the contrast siilarit ap SM(i, efine as L. H + L. H + k SM = L + L. H + H + k Here k is a sall constant ae to tackle the when enoinator approaches 0. In the propose etho, we set k = Note that since the range of values in HDR an LDR is not the sae, we use onl the graient irection to copute SM. The ain avantage of efining SM(i, in this anner is that it reains boune i.e. SM(i, lies in the range [0, 1] with 1 inicating no contrast loss. This copletes the first step of the propose etho. (1) For the secon step, we use the Contrast Liite Aaptive Histogra Equalization (CLAHE). Even though CLAHE operates in an aaptive anner i.e. it perfors histogra equalization base on local iage content, it oes not irectl take into account the loss of contrast ore so in the contet of tone appe iages. In that sense, we can refer to CLAHE as a no reference contrast enhanceent etho since it oes not use an inforation regaring the loss of contrast ue to a particular operation. Because the propose etho provies inforation about contrast loss, it can be consiere as contrast enhanceent with a reference which intuitivel shoul also perfor better than reference free enhanceent. A brief an relevant escription of CLAHE algorith is now provie an the reaer is referre to [1] for coplete etails. For CLAHE algorith, the input iage of size R H is ivie into local regions an for each region histogra is copute. Net, base on a paraeter known as clip liit CL, contrast enhanceent is controlle b liiting the histogra values to the clip liit. Note that a higher clip liit iplies ore contrast. The resultant histogra is then noralize an use to estiate the cuulative probabilit ensit function (cf) which is the apping function fro the original iage patch to the contrast enhance one. In this anner, the contrast of each local region is enhance which are then cobine using bilinear interpolation in orer to eliinate artificiall inuce bounaries. Pertaining to the clip liit, CLAHE uses it liit the slope of the cf which is particularl useful in flat regions of the iage. However, the proble is that CLAHE uses the sae clip liit (efault value being 0.01) for all the iage regions an this ignores the fact TMOs can lea to non-unifor loss of contrast. Hence there is a nee for aaptive eterination of the clip liit. We achieve this b using contrast siilarit ap SM efine in Eq. (1). Since the clip liit an SM follow opposite tren i.e. higher SM eans saller contrast loss while higher CL iplies ore contrast, we efine the aaptive clip CL aaptive liit as CL aaptive = 1 - λ.sm (2) where λ [0,1] is a paraeter that we use to weight SM. A bigger value of λ woul lea to a saller CL aaptive which eans lower contrast enhanceent. To set a proper value for λ, we i a sall pilot subjective stu on the visual qualit of several enhance iages. Iportantl, we foun that sall changes in λ i not result in too large variations of the visual

4 qualit of the resultant iages an even with λ = 1 acceptable results were achieve. So, unlike the clip liit, λ nee not be aaptive an can be fie. For the results reporte in this paper we use λ = 0.97 which seee to provie the best visual qualit for the iages use in the pilot stu. The final step of the propose etho is to check for the naturalness of the enhance iage. This step is require partl ue to the fact that TMOs theselves can result in unnatural iages. Objective easureent of naturalness of an iage is ifficult given that it is highl subjective an involves several aspects that contribute to the overall appearance of the iage to the viewer. Nonetheless, in this paper, we eploe the statistical naturalness easure recentl propose in [7]. It is base on contrast an luinance (brightness) copute using ean an stanar eviation respectivel. For this, histogras of eans an stanar eviations of alost 3000 goo qualit natural LDR iages were plotte. It was foun that these histogras coul be well fitte using a Gaussian an a Beta probabilit ensit functions respectivel where the oel paraeters were eterine via regression. The ensit functions are given b 1 μ P ( ) = ep (3) 2 2πσ 2σ an β 1 α 1 (1 ) P ( ) = (4) B( α, β ) where B(.,.) is the Beta function. The oel paraeters as estiate b regression were μ = , σ = 27.99, α = 4.4 an β = Finall, assuing that luinance an contrast are inepenent, their joint probabilit ensit function will be a prouct of the two. So naturalness was efine as N = 1 P P (5) T where T = a{ P, P } is the noralization factor. So N lies between 0 an 1 with higher value inicating higher statistical naturalness. Since our ai is to copare the naturalness of enhance iages, we efine the ratio of naturalness as N ratio = N propose / N clahe (6) where N propose an N clahe respectivel enote the statistical naturalness of the iage processe b the propose etho (i.e. with aaptive clip liit) an the one processe b CLAHE (fie clip liit). Obviousl, N ratio greater than 1 eans that the propose etho results in iages with ore naturalness at least in the statistical sense. We foun that N ratio was alwas greater than 1 for all the iages that we teste an this works quite well for low contrast tone appe iages. However taking into account the possible liitations of the statistical naturalness easure (which is onl an approiate oel), we epiricall efine a stronger (i.e. bigger) threshol for acceptable qualit iages as 3.5 (an not 1) i.e. when N ratio > 3.5, then no further processing is require. If however, N ratio < 3.5, then the resultant iage was usuall over enhance which tene to look unnatural. So in this case, we eploe the original CLAHE for enhanceent i.e. instea of using CL aaptive we use a sall efault constant clip liit (CL = 0.01) in orer to liit contrast enhanceent. In this wa, the propose etho is ae ore generic an capable of hanling larger contrast ranges an not just low contrast iages. IV. EXPERIMENTAL RESULTS For the eperiental valiation of the propose etho, we selecte 5 HDR iages which were processe b linear TMO (siple linear apping), Ashikiin TMO [2], War TMO [3], Tublin TMO [4], Reinhar TMO [5] an the logarithic TMO. We use the HDR toolbo [6] which provies Matlab ipleentations of these TMOs. The selecte iages are representative of a wie range of content such as inoor an outoor scenes with varing illuination conitions. Although several other TMOs eist, these were chosen because the are popular an cover a wie range in ters of the approach taken to process HDR (soe are siple ones while others eplo ore sophisticate HVS base processing). For eaple the linear TMO is the siplest of the all which perfors a siple linear apping fro the floating point HDR value to [0,255] while the TMO propose b War uses a scaling factor erive fro a pschophsical contrast sensitivit oel to reuce the range. Thus, each of the TMO eploe uses ifferent approaches to naic range reuction an thus leaing to ifferent etents an anner in which contrast loss occurs. Aitionall, linear, logarithic an War TMOs are global (these use a global apping on the entire iage) while the reaining ones are local TMOs (their apping function is base on local iage characteristics). All the TMOs eplo one or ore user efine paraeters an we use the efault values as provie b the respective authors for all but Ashikiin TMO. For this TMO, we foun that the use of efault value resulte in a saturate an ver poor qualit iage an so this value was set to 0.3 for all the iages teste. We obtaine a total 60 enhance iages (5 HDR scenes 6 TMOs 2 contrast enhanceent ethos). We have shown 2 of these iages in Fig. 2 (tone appe b Ashikiin an logarithic TMOs) an zooe in views of soe regions to eonstrate the usefulness of propose schee. The first observation is that the propose etho results in uch better contrast leaing to overall visuall ore appealing iages as shown in Fig. 2 (b), (f). This happens ue to the supervise nature of the propose etho which enables it to ajust the level of contrast enhanceent via the use of CL aaptive. One ajor proble with an TMOs is that the cannot balance the contrast in ark an bright iage areas. With CLAHE this proble cannot be reeie ue to it being non-aaptive. This can be seen fro Fig. 2 (e) where CLAHE iproves contrast in bright areas (ainl foregroun) but unable to o so in the arker areas (ainl the backgroun). The propose schee on the other han provies better contrast restoration in ifferent regions (ark, bright, teture etc.) since it ifferentiates an takes into account the actual

(a) CLAHE (b) Propose (c) CLAHE () Propose (e) CLAHE (f) Propose (g) CLAHE (h) Propose Figure 2. Coparison of iages processe b the propose etho an CLAHE.

2 (c), (), (g) an (h) the zooe in views of iage portions. Observe that the propose etho reners better visibilit of the contents as copare to CLAHE.

visual qualit. In Fig. 2, we provie onl two eaples ue to lack of space. However, the reaer is encourage to ownloa other iages fro the website http://l.perreira.net/ore_eaples.

CONCLUSIONS None of the eisting TMOs can preserve all the contrast an ost of the require use efine paraeters which are usuall content specific.

To tackle this, we propose an aaptive contrast enhanceent strateg base on the loss of contrast between HDR an tone appe iages.

Zuiervel, Contrast Liite Aaptive Histogra Equalization, Graphics Ges IV, Acaeic Press Professional Inc, pp. 474-485, 1994. [2] M.

War, A contrast-base scalefactor for luinance ispla, Graphics Ges IV, Eite b Paul Heckbert, Acaeic Press, pp. 415-421, 1994. [4] J. Tublin, K. Hogins, K.

5 (a) CLAHE (b) Propose (c) CLAHE () Propose (e) CLAHE (f) Propose (g) CLAHE (h) Propose Figure 2. Coparison of iages processe b the propose etho an CLAHE. Zooe in views for highlighte regions are also shown. contrast loss for enhanceent. For better coprehension an a closer look, we have also shown in Fig. 2 (c), (), (g) an (h) the zooe in views of iage portions. Observe that the propose etho reners better visibilit of the contents as copare to CLAHE. Because in general the contrast was iprove for each iage content an all the TMOs use, the propose iea is general an effective strateg for post processing of tone appe iages for better visual qualit. In Fig. 2, we provie onl two eaples ue to lack of space. However, the reaer is encourage to ownloa other iages fro the website for ore visual eaples that eonstrate the effectiveness of the propose schee in coparison to CLAHE. V. CONCLUSIONS None of the eisting TMOs can preserve all the contrast an ost of the require use efine paraeters which are usuall content specific. So the a result in iages with poor contrast an it is not practical to obtain optial paraeters via subjective testing. To tackle this, we propose an aaptive contrast enhanceent strateg base on the loss of contrast between HDR an tone appe iages. Eperiental results eonstrate the effectiveness of the propose iea in enhancing contrast without huan input thereb aking it useful for real tie applications. REFERENCES [1] K. Zuiervel, Contrast Liite Aaptive Histogra Equalization, Graphics Ges IV, Acaeic Press Professional Inc, pp , [2] M. Ashikiin, A tone apping algorith for high contrast iages, 13 th Eurographics Workshop on Renering, Eurographics Association, pp , [3] G. War, A contrast-base scalefactor for luinance ispla, Graphics Ges IV, Eite b Paul Heckbert, Acaeic Press, pp , [4] J. Tublin, K. Hogins, K. Guenter, Two ethos for ispla of high contrast iages, ACM Transactions on Graphics, vol. 18, no. 1, pp , [5] E. Reinhar, M. Stark, P. Shirle, J. Ferwera, Photographic tone reprouction for igital iages, 29th annual conference on coputer graphics an interactive techniques, ACM Press, pp , [6] F. Banterle, A. Artusi, K. Debattista, A. Chalers, Avance High Dnaic Range Iaging: Theor an Practice. ISBN: , AK Peters (CRC Press), Natrick, MA, USA. [7] H. Yeganeh an Z. Wang, Structural Fielit vs. Naturalness - Objective Assessent of Tone Mappe Iages, 8 th International Conference on Iage Analsis an Recognition (ICIAR), pp , 2011.

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