CHANGE DETECTION BY FUSING ADVANTAGES OF THRESHOLD AND CLUSTERING METHODS

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1 The Inernaonal Archves of he Phoograery, Reoe Sensng and Spaal Inforaon Scences, Volue XLII-/W7, 017 ISPRS Geospaal Wee 017, 18 Sepeber 017, Wuhan, Chna CHANGE DETECTION BY FUSING ADVANTAGES OF THRESHOLD AND CLUSTERING METHODS M. Tan *, M. Hao School of Envronen and Spaal Inforacs, Chna Unversy of Mnng and Technology, 1116 Xuzhou Cy, Cosson III, WG III/6 KEY WORDS: Change Deecon, Medu Resoluon, Reoe Sensng, Threshold, Cluserng, Advanage Fuson ABSTRACT: In change deecon (CD) of edu-resoluon reoe sensng ages, he hreshold and cluserng ehods are wo nds of he os popular ones. I s found ha he hreshold ehod of he expecaon axu (EM) algorh usually generaes a CD ap ncludng any false alars bu alos deecng all changes, and he fuzzy local nforaon c-eans algorh (FLICM) obans a hoogeneous CD ap bu wh soe ssed deecons. Therefore, we a o desgn a fraewor o prove CD resuls by fusng he advanages of hreshold and cluserng ehods. Experenal resuls ndcae he effecveness of he proposed ehod. 1. INTRODUCTION The Change deecon (CD) fro reoe sensng ages denfes changes by analyzng uleporal ages acqured n he sae geographcal area a dfferen es, such as land use/land cover, daages due o earhquaes, floods and fres, changes of roads, ces, and plans (Lu e al., 004). In he pas hree decades, los of CD ehods have been proposed o auoacally acheve accurae CD resuls (Hao e al., 014; Moser e al., 011). All ehods can be grouped no supervsed and unsupervsed ypes. The forer deecs changes and supply change ypes by coparng he classfcaon ages of beporal ages. However, needs he ground reference, whch ls s applcaon. The laer denfes changes whou he ground reference, herefore, he sudy n hs paper focuses on he unsupervsed ones. Three seps are usually nvolved: 1) pre-processng, ) age coparson and 3) age analyss (Sngh, 1989). In he frs sep, several correcons need pleenng beween beporal ages o reduce he effecs of lgh and aospherc condon, such as co-regsraon, radoerc correcons (Mshra e al., 01; Ye and Shan, 014). In he second sep, he dfference age s generaed by pxel-by-pxel coparng beween beporal ages. Many ehods have been used o generae he dfference age, ncludng he age dfferencng, age rao, age correlaon, age regresson, log rao for synhec aperure radar (SAR) ages and change vecor analyss (CVA) (Sh e al., 016). In he hrd sep, he dfference age s analyzed and dvded no changed and unchanged pars. In he begnnng, he vsual analyss was appled o deec changes, whch coss uch e and ls he producon effcency (Sader and Wnne, 199). Aferward, a ral-and-error hreshold ehod was pleened by changng he hreshold value, and an eprcal hreshold ehod was developed o denfy changes usng x T, where x s he gray value of he -h pxel, T s a consan, and are he ean and sandard devaon of he dfference age, respecvely (Fung and LeDrew, 1988). In order o prove he effcency, soe auoac hreshold ehods were proposed (Baz e al., 005; Huang and Wang, 1995; I e al., 008). One of he os popular hreshold ehods was proposed by Bruzzone, where he dfference age s supposed as xure Gaussan odel and he Bayes rule for nu error s adoped o calculae he hreshold usng expecaon axu (EM) algorh(bruzzone and Preo, 000). Due o any false alars exsng n he change ap obaned by hreshold, he spaal nforaon was nroduced by soe advanced odels, such as Marov rando odel (Gu e al., 015; Subudh e al., 016),, suppor vecor achne (Neour and Chban, 006), arfcal neural newor (Wang e al., 015; Xu e al., 015), wavele ransfor (Cel and Ma, 011), acve conour odel (Hao e al., 014; L e al., 015) and fuzzy c-eans cluserng (FCM) algorh (Ghosh e al., 011; Krnds and Chazs, 010; Mshra e al., 01). The ranges of pxel gray values n dfference age belongng o he changed and unchanged clusers ofen have overlap, FCM has robus characerscs for abguy and provdes an approprae choce o denfy he by usng fuzzy se nforaon (Ghosh e al., 011). The proved ones anly conan an proved local energy er of explong spaal nforaon. A robus fuzzy local nforaon c-eans (FLICM) was proposed by Krnds and Chazs (Krnds and Chazs, 010) for age segenaon. A novel fuzzy facor was added no FCM o guaranee nose nsensveness and age deal preservaon. Gong e al. (Gong e al., 01) proved he fuzzy facor of FLICM by reshapng he effecs of neghbor pxels on he cener pxel, called reforulaed FLICM (RFLICM), whch proves he ulzng anner of local nforaon by odfyng he fuzzy facor. I s found ha he hreshold ehod,.e., he EM algorh, usually generaes ore false alars bu less ssed deecons han cluserng algorh, such as acve conour odel and FLICM. The EM-based hreshold ehod generaes a CD ap ncludng any false alars bu alos deecng all changes. FLICM obans a CD ap ncludng less false alars. Therefore, we a o desgn a fraewor o prove CD resuls by fusng he advanages of hreshold and cluserng ehods. * Correspondng auhor Ths conrbuon has been peer-revewed. hps://do.org/ /sprs-archves-xlii--w Auhors 017. CC BY 4.0 Lcense. 897

2 The Inernaonal Archves of he Phoograery, Reoe Sensng and Spaal Inforaon Scences, Volue XLII-/W7, 017 ISPRS Geospaal Wee 017, 18 Sepeber 017, Wuhan, Chna The desgned fraewor anly ncludes hree blocs. Frs, CVA s used o beporal ages o produce he dfference age. Second, EM-based hreshold and FLICM are pleened he dfference age and wo nal CD aps are yelded. Then, an advanage fuson sraegy s proposed o fuse wo nal CD aps by ang full use of her advanages and oban he fnal CD ap. Inpu Generae he dfference age Oban nal CD aps Fuson procedure Oupu T 1 age EM-based hreshold CD T age X 1 X Change vecor analyss or age dfferencng FLICM-based cluserng CD Label he CD ap of hreshold Calculae he overlap rao Se he overlap hreshold CD ap Fgure 1. Flowchar of he desgned fraewor.1 EM-based Threshold CD. METHODOLOGY Le X1 and X be wo ulspecral ages acqured fro he sae geographcal area a wo dfferen es. Assung ages have been co-regsered and radoercally correced, he wo ages have he sae sze of M N. The dfference age X s generaed by he agnude of he CVA ehod, and consss of changed pxels W1 and unchanged pxels W. In hs sudy, s assued ha he dfference age X can be seen as a Gaussan xure, as follows: p( X) p( X W ) P( W ) p( X W ) P( W ) (1) 1 1 where p(x), p(x/w1) and p(x/w) are he probably densy funcons of he dfference age X, changed pxels W1 and unchanged pxels W, and P(W1) and P(W) are he a pror probables of changed pxels and unchanged pxels, respecvely. The probably densy funcons p(x/w1) and p(x/w) are Gaussan and can be wren as: 1 ( X ) p X W exp () here (1, ), and are he respecve ean and varance of he correspondng pxels of class W. Gven ha, EM can be perfored o esae he ean values by he followng hree seps (Hao e al., 014). Sep 1: Inalze he eans, covarance and a pror probably P(W). A hreshold d o he dfference age was se o oban he nal changed pxels and unchanged pxels. The hreshold can be generaed fro an eprcal equaon wren as: d R (3) where R s a consan, X and X X X denoe he respecve ean and sandard devaon of he dfference age. The values of, and P(W) can hen be copued fro he classfed pxels and regarded as he nal values o EM. Sep : Expecaon sep. The equaons (1) and () are used o evaluae he a poseror probably P(W/X) wh he equaon (4), as follows: P( W ) p( x W ) P( W x) (4) Px ( ) here 1 and x s he h pxel of he dfference age. Sep 3: Maxzaon sep. Re-esae he paraeers usng he followng equaons: P ( W ) ( ) x 1 ( x ) where he superscrps and +1 are he curren and nex eraons, respecvely. The paraeers are esaed by he seps above and hen checed for convergence. If he convergence creron s no sasfed, repea seps and 3 unl convergence s acheved. Fnally, he ean values are esaed. Fnally, he Bayes rule for nu error s adoped o calculae he hreshold T0 accordng o he followng equaon: T T P. FLICM-based Cluserng CD ln 0 P 1 Dunn (Dunn, 1973) frs developed FCM algorh and laer exended by Bezde (Bezde, 1981). Ths cluserng algorh as a producng and opal c paron hrough an neracve cluserng process. Suppose here are N pxels n he dfference age X x1, x,, xn, and c s he nuber of he clusers. The FCM as a obanng ebershp probably u 0,1 c ( u 1 1,,, N 1 (5) (6) (7) (8) ) of he pxel x n he dfference age for he -h cluser by nzng he objecve funcon as follows: N c 1 1 J u x v (9) where u s he degree of ebershp value of he pxel x n he -h cluser, v s he prooype of he cener of cluser, s he weghng exponen n each fuzzy ebershp, and Ths conrbuon has been peer-revewed. hps://do.org/ /sprs-archves-xlii--w Auhors 017. CC BY 4.0 Lcense. 898

The Inernaonal Archves of he Phoograery, Reoe Sensng and Spaal Inforaon Scences, Volue XLII-/W7, 017 ISPRS Geospaal Wee 017, 18 Sepeber 017, Wuhan, Chna x v s he Eucldean dsance beween objec x and he

Krnds and Chazs (Krnds and Chazs, 010) proposed a robus FLICM cluserng algorh o overcoe he dsadvanages of he absence of spaal nforaon n he nal FCM algorh.

of he -h pxel, N s he nuber of pxels n he dfference age, cener of cluser, u v s he prooype of he denoes he fuzzy ebershp of he -h pxel wh respec o cluser, and for each pxel x, he fuzzy c ebershp

3 The Inernaonal Archves of he Phoograery, Reoe Sensng and Spaal Inforaon Scences, Volue XLII-/W7, 017 ISPRS Geospaal Wee 017, 18 Sepeber 017, Wuhan, Chna x v s he Eucldean dsance beween objec x and he cluser cener v. To prove he robusness of he convenonal FCM, local nforaon has been nroduced o exend. Krnds and Chazs (Krnds and Chazs, 010) proposed a robus FLICM cluserng algorh o overcoe he dsadvanages of he absence of spaal nforaon n he nal FCM algorh. A fuzzy local slary easure facor G was added no FCM, ang o guaranee nose nsensveness and age deal preservaon, and he odfed objecve funcon s wren as where he x N c J u x v G (10) s he gray value of he -h pxel, N s he nuber of pxels n he dfference age, cener of cluser, u v s he prooype of he denoes he fuzzy ebershp of he -h pxel wh respec o cluser, and for each pxel x, he fuzzy c ebershp sasfes he consran ha u 1 1. Addonally, he added local facor s defned as follows 1 G 1 uj x j v (11) d 1 jn j where he -h pxel s he cener of he local wndow, he j-h pxel represens he neghborhood pxels whn he currenly local wndow of he -h pxel, and dj s he spaal Eucldean dsance beween pxels and j. denoes he fuzzy ebershp of he gray value j n ers of he -h cluser, and represens he prooype of he cener of cluser. v.3 Fuson of wo nds of CD Maps r=0.065<t EM ap Label of EM ap Overlap rao FLICM CD ap u j r=0.7063>t Unchanged Changed Overlap No-overlap and rean accurae shapes of changed regons. Therefore, he CD ap of FLICM s adoped o refne he one obaned by he EM hreshold ehod. The flowchar of he spaal advanage fuson sraegy s shown n Fgure. The deals can be found as follows. Sep 1: Label he EM CD ap. For he EM CD ap, he ndependen changed regons are labeled as clusers C C,1 n for he conneced coponens wh four conneced pxels, labeled fro 1 o n, as shown n Fgure 1. Sep : Calculae he overlap rao for each cluser. For he labeled cluser C, he overlap rao r s calculaed referencng he FLICM CD ap usng, where n1 s he pxel r n n 1 nuber n C and n s he nuber of changed pxels n he correspondng regon of FLICM CD ap. Sep 3: Se a hreshold T o he overlap rao r. If r<t, he cluser C reans as changes; n conrary, s reoved as false alars. 3. EXPERIMENTS AND DISCUSSION In order o evaluae he effecveness of he proposed ehod, several experens were carred ou on wo reoely sensed daases. Addonally, four coon ehods were pleened as a coparson, ncludng EM hreshold, fuson of EM and Marov rando feld (EMMRF), ulscale level se (MLS) and FLICM. Four ndces are used o assess he resuls as follows.1) Mssed deecons N ha ndcae he nuber of ncorrecly classfed unchanged pxels n he CD ap. The rao of ssed deecons P s calculaed by P N N0 100%, where N0 s he oal nuber of changed pxels couned n he ground reference ap; ) False alars Nf ha ndcae he nuber of he ncorrecly classfed changed pxels n he CD ap. The rao of false alars Pf s calculaed wh he rao Pf Nf N1 100%, where N1 s he oal nuber of unchanged pxels couned n he ground reference ap; 3) Toal errors N ha ndcae he oal nuber of deecon errors, ncludng boh ssed and false deecons. Ths oal nuber refers o he su of ssed deecons and false alars. Hence, he rao of oal errors P s calculaed wh P ( N N ) ( N N ) 100% ; and 4) Kappa coeffcen f 0 1. The daases used n experens are wo ulspecral ages acqured by he Landsa Enhanced Theac Mapper Plus (ETM+) sensor of he Landsa-7 saelle n an area of Mexco n Aprl 000 and May 00, and a secon of pxels was seleced as a es se. The changes were caused by a fre ha burned a large par of he vegeaon n he es regon. Fgure 3(a) and (b) show he band 4 of 000 and 00 ages, respecvely. A reference ap was anually obaned by a dealed vsual analyss of boh he avalable uleporal ages and he dfference age as shown n Fgure 3(c). Fused CD ap 1 Fgure. Flowchar of he spaal advanage fuson sraegy In hs sudy, s supposed ha changes usually occur as a regon n reoe sensng ages. For CD ehods ncorporang conexual nforaon, hey usually ss changes around edges because of over-use conexual nforaon, such as FLICM. The EM-based hreshold ehod can deec alos all changes (a) (b) (c) Fgure 3. Band 4 of daases acqured n (a) Aprl 000 and (b) May 00, (c) ground reference ap Ths conrbuon has been peer-revewed. hps://do.org/ /sprs-archves-xlii--w Auhors 017. CC BY 4.0 Lcense. 899

4 The Inernaonal Archves of he Phoograery, Reoe Sensng and Spaal Inforaon Scences, Volue XLII-/W7, 017 ISPRS Geospaal Wee 017, 18 Sepeber 017, Wuhan, Chna Fgure 4 shows he CD aps obaned by EM, MRF, MLS, FCM, FLICM and he proposed ehod, respecvely. The values of he paraeer n EMMRF and μ n MLS were se o 1.6 and 0., and he overlap hreshold T n he proposed ehod was se o 0.3. As can be seen n Fgure 4(a), he change ap of EM conans alos all changes, bu any false alars exs a he sae e (e.g., crcle regon). EMMRF gves hoogeneous regons by usng spaal conex, bu uch dealed nforaon s reoved and los of spos sll exs as shown n he crcle regon of Fgure 4(b). Ths s explaned by he facor ha depends on he nal CD ap of EM and neglecs he fuzzy spaal nforaon. The resuls of MLS conan los of spos as presened n Fgure 4(c), and he reason s ha clusers whou consderng spaal nforaon. In conras, FLICM gves ore hoogenous CD aps han MLS due o ncorporang local nforaon, bu ssed soe dealed changes due o he overuse of spaal nforaon. However, he proposed ehod can reove false alars ore effcenly as shown n he crcle regons of Fgure 4(e) and generaes he os slar CD ap o he ground reference aong all he ehods n hs sudy. The reason s ha he proposed ehod reduces he false alars exsng n he EMbased resuls by ang advanage of he ones of FLICM. In suary, he proposed ehod supples an effecve ehod for unsupervsed change deecon. effecveness of he proposed ehod ha reoves false alars and preserves dealed changes. Mehod Table 1. Quanave CD resuls Mssed deecons False alars Toal errors No. No. P f No. P EM EMMRF MLS FLICM Proposed CONCLUSION A fraewor of fusng advanages of hreshold and cluserng ehods o reove false alars and preserve dealed changes sulaneously. Experens were conduced on Landsa EMT+ daa ses o deonsrae he perforance of proposed ehod. The oal errors and appa coeffcen obaned by he proposed ehod are 3601 and Copared wh soe sae-of-hear ehods (.e., EM, EMMRF, MLS, and FLICM), he proposed ehod acheves proveens n boh accuracy and vsual nerpreaon. Resuls ndcae ha proposed ehod no only obans ore hoogenous CD aps bu preserves ore dealed feaures han oher ehods n hs paper. In oal, he proposed ehod provdes an effecve unsupervsed CD ehod fro reoe sensng ages. P ACKNOWLEDGEMENTS (a) (b) (c) The wor presened n hs paper s suppored by he Naural Scence Foundaon of Jangsu Provnce under Gran BK REFERENCES (d) (e) (f) Fgure 4. CD resuls of daases obaned by (a) EM, (b) EMMRF, (c) MLS, (d) FLICM, (e) proposed ehod, and (f) s he ground reference ap. Table 1 presens he accuracy coparsons of ssed deecons, false alars, oal errors and appa coeffcen aong hese seven ehods. EM resuls n he axu false alars of 979 pxels, and EMMRF generaes he nu ssed deecons of 796 pxels and false alars of 5076 pxels, whch reduces ssed deecons and false alars copared wh EM by ncorporang spaal nforaon. MLS produces he ssed deecons of 4071 pxels, bu MLS obans less false alars han EM and EMMRF. For FLICM, reduces any false alars copared wh EM due o he nroducon of local nforaon, where he oal errors are 4947 pxels. I s worh nong he proposed ehod obaned he os accurae CD resuls aong all ehods used n hs sudy va he oal errors and appa coeffcen, and he ssed deecons, false alars, and oal errors are 137, 9 and 3601, respecvely. More poranly, resuls n fewer ssed deecons han FLICM and uch less false alars han EM, whch ndcaes he Baz, Y., Bruzzone, L., Melgan, F., 005. An unsupervsed approach based on he generalzed Gaussan odel o auoac change deecon n uleporal SAR ages. IEEE Transacons on Geoscence and Reoe Sensng, 43(4), pp Bezde, J.C., Paern recognon wh fuzzy objecve funcon algorhs. Kluwer Acadec Publshers, Norwell, MA, USA. Bruzzone, L., Preo, D.F., 000. Auoac analyss of he dfference age for unsupervsed change deecon. IEEE Transacons on Geoscence and Reoe Sensng, 38(3), pp Cel, T., Ma, K.K., 011. Muleporal Iage Change Deecon Usng Undecaed Dscree Wavele Transfor and Acve Conours. IEEE Transacons on Geoscence and Reoe Sensng, 49(), pp Dunn, J.C., A fuzzy relave of he ISODATA process and s use n deecng copac well-separaed clusers. Journal of Cybernecs, 3(3), pp Fung, T., LeDrew, E., The deernaon of opal hreshold levels for change deecon usng varous accuracy ndces. Phoograerc Engneerng and Reoe Sensng, 54(10), pp Ghosh, A., Mshra, N.S., Ghosh, S., 011. Fuzzy cluserng algorhs for unsupervsed change deecon n reoe sensng ages. Inforaon Scences, 181(4), pp Gong, M., Zhou, Z., Ma, J., 01. Change Deecon n Synhec Aperure Radar Iages based on Iage Fuson and Ths conrbuon has been peer-revewed. hps://do.org/ /sprs-archves-xlii--w Auhors 017. CC BY 4.0 Lcense. 900

5 The Inernaonal Archves of he Phoograery, Reoe Sensng and Spaal Inforaon Scences, Volue XLII-/W7, 017 ISPRS Geospaal Wee 017, 18 Sepeber 017, Wuhan, Chna Fuzzy Cluserng. IEEE Transacons on Iage Processng, 1(4), pp Gu, W., Lv, Z., Hao, M., 015. Change deecon ehod for reoe sensng ages based on an proved Marov rando feld. Muleda Tools and Applcaons, pp Hao, M., Sh, W.Z., Zhang, H., L, C., 014. Unsupervsed Change Deecon Wh Expecaon-Maxzaon-Based Level Se. IEEE Geoscence and Reoe Sensng Leers, 11(1), pp Huang, L., Wang, M., Iage hresholdng by nzng he easures of fuzzness. Paern Recognon, 8(1), pp I, J.H., Jensen, J.R., Hodgson, M.E., 008. Opzng he bnary dscrnan funcon n change deecon applcaons. Reoe Sensng of Envronen, 11(6), pp Krnds, S., Chazs, V., 010. A Robus Fuzzy Local Inforaon C-Means Cluserng Algorh. IEEE Transacons on Iage Processng, 19(5), pp L, H., Gong, M., Lu, J., 015. A Local Sascal Fuzzy Acve Conour Model for Change Deecon. IEEE Geoscence and Reoe Sensng Leers, 1(3), pp Lu, D., Mausel, P., Brondzo, E., Moran, E., 004. Change deecon echnques. Inernaonal Journal of Reoe Sensng, 5(1), pp Mshra, N.S., Ghosh, S., Ghosh, A., 01. Fuzzy cluserng algorhs ncorporang local nforaon for change deecon n reoely sensed ages. Appled Sof Copung, 1(8), pp Moser, G., Anga, E., Serpco, S.B., 011. Mulscale Unsupervsed Change Deecon on Opcal Iages by Marov Rando Felds and Waveles. IEEE Geoscence and Reoe Sensng Leers, 8(4), pp Neour, H., Chban, Y., 006. Mulple suppor vecor achnes for land cover change deecon: An applcaon for appng urban exensons. ISPRS Journal of Phoograery and Reoe Sensng, 61(), pp Sader, S., Wnne, J., 199. RGB-NDVI colour coposes for vsualzng fores change dynacs. Inernaonal Journal of Reoe Sensng, 13(16), pp Sh, W., Shao, P., Hao, M., He, P., Wang, J., 016. Fuzzy opology based ehod for unsupervsed change deecon. Reoe Sensng Leers, 7(1), pp Sngh, A., Dgal change deecon echnques usng reoely-sensed daa. Inernaonal Journal of Reoe Sensng, 10(6), pp Subudh, B.N., Ghosh, S., Nanda, P.K., Ghosh, A., 016. Movng objec deecon usng spao-eporal ullayer copound arov rando feld and hsogra hresholdng based change deecon. Muleda Tools and Applcaons, pp Wang, Q., Sh, W., Anson, P.M., L, Z., 015. Land cover change deecon a subpxel resoluon wh a Hopfeld neural newor. IEEE Journal of Seleced Topcs n Appled Earh Observaons and Reoe Sensng, 8(3), pp Xu, D., Rcc, E., Yan, Y., Song, J., Sebe, N., 015. Learnng deep represenaons of appearance and oon for anoalous even deecon. arxv preprn arxv: , pp. Ye, Y., Shan, J., 014. A local descrpor based regsraon ehod for ulspecral reoe sensng ages wh non-lnear nensy dfferences. ISPRS Journal of Phoograery and Reoe Sensng, 90, pp Ths conrbuon has been peer-revewed. hps://do.org/ /sprs-archves-xlii--w Auhors 017. CC BY 4.0 Lcense. 901

Learning Objectives. Self Organization Map. Hamming Distance(1/5) Introduction. Hamming Distance(3/5) Hamming Distance(2/5) 15/04/2015

Learning Objectives. Self Organization Map. Hamming Distance(1/5) Introduction. Hamming Distance(3/5) Hamming Distance(2/5) 15/04/2015 /4/ Learnng Objecves Self Organzaon Map Learnng whou Exaples. Inroducon. MAXNET 3. Cluserng 4. Feaure Map. Self-organzng Feaure Map 6. Concluson 38 Inroducon. Learnng whou exaples. Daa are npu o he syse