Determining Conjugate Points of An Aerial Photograph Stereopairs Using Separate Channel Mean Value Technique

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1 ITB J. En. Sc. Vol. 41, No. 2, 2009, Determnn Conuate Ponts of An Aeral Photoraph Stereopars Usn Separate Channel Mean Value Technque Andr Hernand 1, D. Muhally Hakm 1, Irawan Seomarto 1, Aun Budharto 1 & Emala 2 1 Faculty of Earth Scences and Technoloy- ITB 2 Alumnus of Faculty of Earth Scences and Technoloy- ITB Abstract. In the development of dtal photorammetrc system, automatc mae matchn process play an mportant role. The automatc mae matchn s used n fndn the conuate ponts of an aeral photoraph stereopar automatcally. Ths matchn technque ves qute snfcant contrbuton especally n the development of 3D photorammetry n an attempt to et the exact and precse toporaphc nformaton durn the stereo resttuton. There are two mae matchn methods that have been so far developed,.e. the area based system for ray level envronment and the feature based system for natural feature envronment. Ths research s tryn to mplement the area based matchn wth normalzed cross correlaton technque to et the correlaton coeffcent between the spectral value of the left mae and ts par on the rht. Based on the prevous researches, the use of color mae could ncrease the qualty of matchn. One of the color mae matchn technque s known as Separate Channel Mean Value. In order to be able to see the performance of the technque, a number of sampln areas wth varous dfferent characterstcs have been chosen,.e. the heteroeneous, homoeneous, texture, shadow, and contrast. The result shows the hhest smlarty measure s obtaned on heteroeneous sample area at sze of all reference and search mae,.e. (11 pxels x 11 pxels) and (23 pxels x 23 pxels). In these area the correlaton coeffcent reached more than 0.7 and the hhest percentae of smlarty measure s obtaned. The averae of total smlarty measure of conuate maes n the sampln mae area only reach about % of success. Therefore, ths technque has a weakness and some treatment to overcome the problems s stll needed. Keywords: area-based matchn; conuate ponts; correlaton coeffcent; mae matchn; photorammetry. 1 Introducton A fundamental problem n photorammetrc system s the reconstructn of the 3D data from an aeral photoraphy stereopars. For example, part of photorammetrc process such as relatve orentaton, absolut orentaton, aeral eceved February 10 th, 2009, evsed March 3 rd, 2009, Accepted for publcaton July 30 th, 2009.

2 142 Andr Hernand, et al. tranulaton, orthophoto and dtal terran model (DTM) eneraton. Unfortunately, the analoue approach of those process are tme consumn and the results are dependn upon the operator skll. To overcome the problems the human tasks are radually replaced by the dtal computer. Ths paper descrbed part of the dtal system to establsh an automatc photorammetrc process,.e. the utlzaton of dtal mae processn. Human vson has the capablty to search conuate ponts or obects whch appear n overlapn area of an aeral photoraph stereopar e.. determnaton of sx pars of conuate otto von ruber ponts n left and rht photoraph n relatve orentaton process. To that end, s actually a searchn process base on pattern reconton method. The process of fndn out the conuate ponts (or obects) n two or more overlappn photoraphs s a fundamental process n photorammetrc system. In dtal doman, ths process can be done automatcally, known as mae matchn method [1]. The developments of mae matchn technque n the feld of photorammetry has qute lon hstory. Frst experments started n the fftes by Hobrouh [2] untl reseachers have been tryn to make every snle effort to fnd out the best mae matchn technque. Despte consderable effort, no eneral soluton was found. A queston arses amon the researchers how the human vson s able to fnd conuate ponts easly wthout a lot of effort. Ths s ust an example n shown the complety of the human vson n solvn the problem easly. The mae processn doman partcularly n photorametrc applcaton related to the mae matchn can be dvded nto two : the area-based and the feature based matchn methods. Area-based matchn method s more popular compare to feature-based matchn method, because of hstorcal reasons. Area-based matchn s assocated wth matchn the ray values. The ray level dstrbuton of small areas of two maes, called mae patches, s compared by correlaton or least-square technques. Snce the maes contan of full 24-bt color nformaton, the above technques could be modfed when applyn the ray-value mae. Two ways have been nserted nto the correlaton technques, resultn n one snle smlarty value. The other approach calculates each channel separately and allows ndvdual assessment. Ths research applyn a mean value of three channels as smlarty value. Ths technque has been known as Separate Channel Mean Value Correlaton [3]. Kuzu [3] has mplemented ths technque for volumetrc obect reconstructon purpose. Ths technque has been used to refne the vsual of the obect reconstructon. Furthermore, ths technque has been expermented n fndn conuate ponts or natural obects n a number of sample of aeral photoraphs havn dfferent characterstcs.

3 Conuate Ponts of An Aeral Photoraph Stereopars 143 The man obectve of ths research s nvestatn method to mplement mae matchn procedure, partculary color nformaton consderaton n an maes, usn separate channel mean value correlaton technques on aeral photoraph. The result of ths research are expected to ve real contrbuton for mprovement mae matchn methods whch can be used for wde applcatons of automatc eoraphc extracton n dtal photorametrc (DTM, toporaphc features complaton, etc.). Partcularly for supportn the early process of photorametrc method those are determnaton sx otto von ruber ponts. 2 Area-Based Matchn Method Area-based matchn usually work based on local wndows or mae patches. The mae patches consst of reference mae, search mae and sub-search mae. The reference mae s usually kept n a fxed poston wthn one of the selected mae. The sub-search mae s a movn mae patches n the search mae havn equal sze wth reference mae. The sub-search maes are compared to the reference mae. The comparson s performed wth dfferent smlarty measure based on correlaton or least-squares technques [4]. The concept of area-based matchn showed n Fure The Correlaton Technque Fure 1 Concept of area-based matchn. The correlaton s the most famlar technque n fndn the conuate ponts n photorammetrc applcaton. The man dea of the correlaton technque s to measure the smlarty between reference mae and search mae by computn

4 144 Andr Hernand, et al. the correlaton coeffcent. The correlaton coeffcent (ρ) s computed usn the follown formula: where : ρ : correlaton coeffcent (-1 ρ +1). : covarance of mae patches (reference mae) and (subsearch mae) : standard devaton of mae patch (reference mae) : standard devaton of mae patch (sub-search mae) Introducn the mae functon x, x y (1), for the left and rht mae pacthes (reference and sub-search mae) and ther means x y x to equaton (1) produced :,, n m 1 1 n m n m The correlaton coeffcent (ρ) s determned for every row and colum poston of the sub-search mae wthn the search mae. The next step s to determne the poston of the sub-search mae havn the mamum correlaton coeffcent. 2.2 Separate Channel Mean Value Snce the mae contan color nformaton, the equaton (2) can be modfed usn a mean value of three channels as snle smlarty measure. Ths technque s knowns as Separate Channel Mean Value Correlaton [3]. et ρ red, ρ reen and ρ blue are the correlaton coeffcents for red, reen and blue respectvely; furthermore : ρ Total red reen blue Total (3) 3 s the total corelaton coeffcent as one snle smlarty measure calculated from mean value of three channels. Havn computed for all poston of the sub-search mae then the total correlaton coeffcent s chosen from the (2)

5 Conuate Ponts of An Aeral Photoraph Stereopars 145 one havn the mamum correlaton coeffcent. Two obects on the mae can be rearded as two same obects f the correlaton coeffcent s between 0.7 to 1.0 [5]. 3 Expermental Works For the purpose of ths research two overlapped aeral color photoraphs of Sabua area - ITB campus has been used. The overlappn area s consdered havn dfferent terran charactertstcs,.e. homoeneous, heteroenous, shadow, texture densty, and contrast. Ths aeral photoraphs have been taken from aeral photoraphy msson by Cessna arcraft wth 68% overlap. See Fure 2. Fure 2 esearch area on overlaped aeral photoraph of Sabua. The sstematc steps of work n carryn out ths experment are as follow: 1. Identfyn appromate locaton of conuate ponts based on varous dfferent characterstc (homoeneous, heteroenous, shadow, texture densty, and contrast) and dstance from prncple ponts on an aeral photoraph stereopars. 2. Exctractn mae patches (reference mae and search mae) wth dfferent szes from aeral photoraph stereopars. 3. Computn correlaton coeffcent of each mae patches usn separate channel mean value correlaton technque.

6 146 Andr Hernand, et al. 4. Analyze the smlarty measure usn mamum correlaton coeffcent of each mae patches. Determnaton of appromate locaton of the conuate ponts on the overlappn photoraphs was done vsually. The locaton of the ponts are chosen by consdern the dfferent obect characterstcs and havn varous dstances from aeral photoraph prncpal pont. The overlappn area s devded nto nne samples area, see Fure 2. For each par of sample contans of three dfferent sze (11 pxels x 11 pxels), (21 pxels x 21 pxels), (33 pxels x 33 pxels) as reference mae assosated wth three dfferent sze (23 pxels x 23 pxels), (53 pxels x 53 pxels), and (83 pxels x 83 pxels) of search mae respectvely. In ths experment, the correlaton coeffcents are computed usn Equaton 3 for all rd samples, and the result can be seen Table 1. Table 1 Mamum correlaton coeffcents and smlarty measures to varous dfferent obect characterstc. No. Obect Characterstc Sze of Sze of Smlarty Correlaton eference Search Measure Coeffcent Imae (pxels) Imae (pxels) (%) 11 x 11 23x % 1 Homoenous 21 x 21 53x % 33 x 33 83x % 11x11 23x % 2 Heteroenous 21x21 53x % 33x33 83x % 11x11 23x % 3 Texture 21x21 53x % 33x33 83x % 11x11 23x % 4 Shadow 21x21 53x % 33x33 83x % 11x11 23x % 5 Contrast 21x21 53x % 33x33 83x % Averae of Total Smlarty Measure % As llustrated n Table 1, the averae of total smlarty measure of varous dfferent obect characterstcs s about 41,43 % of success. The hhest smlarty measure s obtaned on heteroenous area lead to about 75 % %, and the other characterstcs area s conversely. In ths heteroentc area, the obects are easer to dentfy.

7 Conuate Ponts of An Aeral Photoraph Stereopars 147 Usn separate channel mean value technque to be mplemented to both varous dfferent characterstc shows averae of total smlarty measure of conuate mae reaches to about % of success. 4 Concluson Determnn conuate ponts of an aeral photoraph stereopars usn separate channel mean value technque wll be succeed f the method s appled to heteroenous area. The smlarty measure obtaned on heteroenous area s about 75 % %. These areas have mamum correlaton coeffcent of more than 0.7 and the hhest procentae of smlarty measure. All expermental result usn separate channel mean value technque show that the averae of total smlarty measure s only reach % of success. Ths mean that the technque may be has a weakness. One of the suestons to et a better result s by alnn the two photoraphs wth respect to the prncpal ponts such as eppolar lne creaton before matchn process. Furthermore, the aeral photo maes have also many weaknesses radometrcally (nose, msalnment, etc.), therefore radometrc correctons are needed. Acknowledment These authors would lke to thank to ITB esearch Grant (No. 081/K01.18/P/2008) for fnancal support on ths research. eferences [1] Schenk, T., Dtal Photorammetry, I, Terrascence, aurelvlle OH, USA, 428 p, [2] Hobrouh, G., Automatc Stereoplottn, Photorammetrc Enneern and emote Sensn, 25(5), pp , [3] Kuzu, Y., Photorealstc Obect econstructon Usn Color Imae Matchn, Internatonal Archves of Photorammetry, emote Sensn and Spatal Informaton Scences, ISPS Commson V Symposum, Corfu, 34(5), pp , [4] Ackermann, F., Dtal Imae Correlaton: Perfomance and Potental Applcaton n Photorammetry, The Photorammetrc ecord, 11(64), pp , [5] Wolf, P.. & Dewtt, B. A., Elements of Photorammetry wth Applcaton n GIS,3th Edton, McGraw-Hll, Boston, USA, 624 p, 2000.