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(1)Jour. Korean Earth Science Society, v. 26, no. 1, p. 58−65, February 2005. J

(2). *9'ç # æ\>Ò 'ç¶ò~ ^ÎÖc j8ç Ï ~\' *Á8ö Á²÷L. *Þ&v æ"v/", 151-748 *Þßê &k âÿ Ö 56-1 2 9&v ;¦, 136-792 *Þßê 9§ â.ÿ 3 389. 1. Application of Homomorphic Filtering to Satellite Imagery and Geophysical Image Data Hee-Young Yoo1,*, Kiwon Lee2 and Byung-Doo Kwon1 . 'HSDUWPHQW RI *HRVFLHQFH (GXFDWLRQ 6HRXO 1DWLRQDO 8QLYHUVLW\ 6DQ 6KLOOLPGRQJ *ZDQDNJX 6HRXO .RUHD 'HSDUWPHQW RI ,QIRUPDWLRQ 6\VWHPV +DQVXQJ 8QLYHUVLW\ 6DPVHRQGRQJ JD 6XQJEXNJX 6HRXO .RUHD. $EVWUDFW Homomorphic filtering improves image by enhancing high components and reducing low components in the frequency domain based on FFT, as one of useful digital image processing techniques. In this study, the application program for homomorphic filtering was developed. Using this program, satellite imageries and geophysical image such as magnetic image data were processed and their results were analyzed. In case of applying to other techniques such as histogram equalization and kernel-based masking for the same purpose, they often cause the slight distortion of boundary or overall change of brightness values on the whole image. Whereas, homomorphic filtering has ability to enhance selectively detailed components in a target image. Therefore, this technique can be effectively used for extraction or separation of complex types of characteristics contained in the satellite imagery. In addition, this technique would be applicable to investigate anomalous zone in various geophysical image data. ,FZXPSET Homomorphic filtering, High-resolution imagery, Geophysical image, Image Enhancement º £ ^ÎÖc j8çf Òö æ~ö V.¢ z V»b "2> 'öB &"2 ^º £zÊ "2 ^ º ;z~ 'ç~ &j N¢ ;zÊº ¾ÒV» . öBº ^ÎÖc j8çj * wÏ *Îj BB ~ *W'ç" æ>Ò ¶KöÒ ¶ò¢ æz 'çö þ'b 'Ï~ Ö"¢ ªC~& . 'ç ïz V»¾ $ îÊ ¾Ò " ?f 'ç;z V»öBº ºÂ &Ë ãê¦~ *~¢ æzÊ¾ 'ç~ z²8 *Ú 'çj &çb æzÊº >ö ^ÎÖc j8çf ^¦' 'ç ;~ ÚÏj F'b ; > ® . ^ÎÖc j8çf *W 'çöB Ç æ;æ>~ ßWj ºÂ~¾ ªÒ~º Î"' O»b ¾æÒb æ>Ò 'ç¶òöB ç&¢ Ò~º ãÖöê FÏ~² 'ÏF > ®j ©b 'B . ºÚ ^ÎÖc j8ç, çê 'ç, æ>Ò 'ç, 'ç ;z. * V ", >ï çê 1 m ~~ çê *W'ç ~ "* Ï &ËæB V~ 7Á& çê 'ç ¾Ò V»j j~º ¾Ò O»¾ ªC V *Corresponding author: [email protected] Tel: 82-2-878-7233 Fax: 82-2-874-3289. »~ jºW &v> ® . $ '. ªC V »j 'Ï~ · bB¦V áÚæº 'çö >Ú ®º ;¢ ºÂ~º © ¢>' 'ç ¾Ò~ Ï'æ ' ¾Ò êê V~ O» ¾ rÒ¾j 'Ï~ ^B6¾ Ö Onj d º ";ê 7º~² > ® (Jensen, 1996). ÿËö V¢ öBº "2> 'ö B 'çj ;z r FÏ O»b rJê ^Î.

(3) *9'ç5æ>Ò'ç¶ò~^ÎÖcj8çÏ. Öc jVç V»j *W 'ç¶òf æbÒ Gç öÒ ¶òö '' 'Ï~ Ö"¢ ªC~& . V B 'ç ;z¦ ²~ ¾ ¶ òb ö ¶òö B CÚ ;¢ Î"'b ª~¾ ê~ê ~º z² ;~ ¾Ò";j ~~æ 'ç;z ¾Ò~ Ö" 'ç~ ïç &jN¾ z² ª ·ç æz~² B . ¢>'b 'ç;z V»öº ®ÊÆÎ ïz O»(Histogram Equalization)¾ 6 îÊ(Kernel Mask) ¾Òf ?f * '~ jVç O» Ï>Ú z . ö j ^ÎÖc jVçf ö V~ Òö æ~j >¯ Êö "2> 'ö B "2 Wªf ;z~ &"2 Wªf ç&'b £zB 'çÚ~ ïç &j¢ ;~º ©. (Myler and Weeks, 1993; Parker, 1997; Gonzalez and Woods, 2002). *Òræº V~ çë' *W 'ç¾Ò ZöB ç7'b ^ÎÖc jV¢ B~æ pV r^ö öB .êÖ V>~ wÏ *Îj î BB~ þö 'Ï~& . $ ÿ¢ ~ ' ç ¶òö &~ ®ÊÆÎ ïz V»" ãêF ;z(Sharpening) * jVçj 'Ï ê ^ÎÖc jVç Ö"f NÖ j Û~ ç7 jv~ Ö"¢ ªC~& . Þ jVç V»j F ºÂ V»" ê~º ¾Ò ";j .~V *~ jV ç ¾Ò ê ºÂB F~ ;{ê¢ þ B~ & .. f(x, y) = i(x, y)Ür(x, y) 0 < i ( x, y ) < ∞ 0 < r ( x, y ) < 1. V BL 'çf 2Nö > f(x, y) ;~ > ® . * ²(x, y)öB > f~ 8f 6öB~ 'ç~ C V(Brightness Value: BV) $º «zê¢ ~ . ~¾~ Ë(Scene)j º 'ç ; f(x, y)º v &æ Wªb ª > ®º º '' Ë b «ÒB ^ö «~ ·" Ëö ®º b ÚöB >ÒB «~ · . ©j '' « (Illumination), >Ò(Reflectance) Wª¢ ¦ ' ' i(x, y), r(x, y) V . VB >Ò æ>& 0 " 1 ãÖöº '' j* >f j* >Ò¢ ~ .. (1). «" >Ò Wª~ b * ãÖ Òö æ ~j ê «" >Ò Wªj ªÒ > ìV r^ ö Òö æ~j >¯~V *ö ö V( (1)) j (2)f ? îÚ 8b 'Ï~ê . z(x, y) = In f(x, y) z(x, y) = In i(x, y) + In r(x, y). (2). ¢ 8j Òö æ~ " Ö"¢ (3)" ? Z(u, v) ¾æÞ . Òö æ~ ê "2> 'öB (4)f ?f jV > H(u, v) (Fig. 1)¢ ~( (5)), Òö æ~( (6))j ~ * 'b æ~ Úê . ~ Öj * (7)" ? æ> >¢ " 'ç ;z ¾Ò";b ;B 'ç ¢ áj > ® ² B . ℑ {z(x, y)} = ℑ {In f(x, y)} {z(x, y)} = ℑ {In i(x, y)} + ℑ {In r(x, y)} Z(u, v) = Fi(u, v) + Fr(u, v) H(u, v) = ( γH – γL )[ 1 – e. 2. 2. –c ( D (u, v ) ⁄ D0). ] + γL. S(u, v) = H(u, v)Z(u, v) S(u, v) = H(u, v)Fi(u, v) + H(u, v)Fr(u, v). (3) (4). (5). s(x, y) = ℑ {H(u, v)Fi(u, v)} + ℑ {H(u, v)Fr(u, v)} (6) s(x, y) = i '(x, y) + r '(x, y) –1. ^ÎÖc j8ç +RPRPRUSKLF ILOWHULQJ

(4). . g(x, y) = es(x, y) g(x, y) = ei '(x, y)Áer '(x, y). –1. (7). 'ç~ « Wªf ¢>'b *' æz& ' , >Ò Wªf jÝ~æ pf CÚ~ vN6öB 7 ·Ê#² æz~º ãË ® . ßû f 'çö B Òö æ~j Û "2> 'b æ~ B ê &"2>º «" "2>º >ÒWª" ' ' &>º ©b ªC~º © &Ë~ê . ^ÎÖc jVçj Ï~ «" >Ò Wªö & ôf BÚ& &Ë~ . BÚº Òö æ~~ &"2 5 "2 Wªö Ob ' Ëj ~º jV > H(u, v)ö ~ &Ë~ . ò £ γL < 1 γH > 1 >² F> &"2 Wªö.

(5) . ~\'Á8öÁ²÷L. Fig. 1. Cross section of a circularly symmetric filter function./ D(u, v) denotes the distance from the origin of the centered transform.. Fig. 2. Implementation for homomorphic filtering and its user interface.. ~ ò Úæº Ö"¢ 6²Ê "2 Wªö ~ ò Úæº Ö"¢ ÃÊº ãË ® . *Î BB ^ÎÖc jVçf V~ *W 'ç¾Ò *Î öB æö~ ®æ pV r^ö öBº . êÖ ~ãöB ¢ ¾Ò > ®º ²*ÞÚ¢ BB~& . jVç ";ö jº «K æ> j Ò Ï¶& ç7 «K~ê ~º V¾Ê¢ B~. · þ" 'Ï &Ë~ê ~& (Fig. 2).. \ Ö æ>~ æzö 8 Ö ª+ ^ÎÖc jVç ";öB «K æ>ö V Ö". 'ç~ N¢ jv~V *~ ãVê Î·" æ j R' >ï çê 6.6 m~ *;ï(Panchromatic) 'çj B~º KOMPSAT EOC bB~ ¦ª 'ç j Ï~ ªC~& . Ö"¢ Û æ>& ¢öö V¢ Ö" 'ç ·çj ®rj { > ® . Fig. 3(b)f Fig. 3(c)¢ jv~ γL 0.8öB 0.9 æö V¢ Ö"& ¢æº ©j { > ®. . γL8 æ 'ç~ z² ª¢ ·~ OËb ÿÊº 'Ëj "Ú *Ú'b Cjê . Fig. 3(d)f Fig. 3(f)¢ jv~ γH8ö V æz¢ r > ®º γH8 î> Cf æ~ &jN&. ê . Fig. 3(c)f Fig. 3(d)¢ jv~ D08ö V N ¢ jv > ®º D08 > Cf ¦ª~ ' z 9² ¾æ¾º ©j { > ® . c8 ~ Nö V æz ·çj rV *Bº Fig. 3(c)f 3(e)¢ {~ B . c8 î> Cf ¦ª" ÚvÚ ¦ª~ 8~ æz& º ©j { > ® . Cf ¦ªf z× Cjæ ÚvÚ ¦ ªf z Úvò &j& æ² B . ^ÎÖc jVº "2>¢ ; º GöB "2> Û" jV(High Pass Filter)f Ö FÒ~. . ¾ "2> Û" jVº "2> 'öB "2>ò ÎV &"2>º B~º > ^ÎÖ c jVº "2º z ;z~ &"2º B~º © jî¢ £zB ¦ z ^&~² "2> ' öB . &Ë~ . Væ O»~ Ö 'ç jL öBº &¦ª~ 'ç ¾Ò ZöB B~ ®º 'ç ;z V» ®ÊÆÎ ïz O» " * 'öB~ 6 îÊ¢ Ï * jV¢ 'çö 'Ï~ Ö"¢ ^ÎÖc jVç 'Ï Ö"f jv~& . þöBº ãVê Ò ³ê ªV6 ¦"~ IKONOS 1 m ¦ª 'ç (Fig. 4(a))j Ï~, 6~ V¢ 3Ü3b J; * jV(Fig. 4(b)), ®ÊÆÎ ïz(Fig. 4(c)) Ò «Kæ>¢ γH = 2, γL = 0.9, c = 1, D0 = 10 ~ ^ÎÖc jVç(Fig. 4(d))j '' >¯~ & .. * jVç >¯ Ö"(Fig. 4(b))¢ ö 'ç (Fig. 4(a))" jv ãê ¦ª ¦ z ;z>.

(6) *9'ç5æ>Ò'ç¶ò~^ÎÖcj8çÏ. . Fig. 3. The results of homomorphic filtering with KOMPSAT EOC imagery according to variables. The original image is (a). (b) is the homomorphic filtering result where γH=2, γL=0.8, c=0.5 and D0=20. (c), (d), (e) and (f) is the image where γH=2, γL=0.9, c=0.5 and D0=20, where γH=2, γL=0.9, c=0.5 and D0=10, where γH=2, γL=0.9, c=1 and D0=10, and where γH=3, γL=0.9, c=0.5 and D0=10, respectively.. Ú ¾æÎj r > ® . ~æò ºÂ~¶ ~º & ç CÚ~ Vã æ z²8 Ôf æb > Ú ®º ãÖ &ç CÚ~ *' ßWj Ïª® *~æ á~º ãÖ& ®b 6 îÊ Úö B Î z²8j Ï~ 7ö *~ &ç z²8j Ö Ö"¢ &Ú~º OV r^ö ã ê~ *~& æ *þ ® . Þ ®ÊÆÎ ï z Ö"(Fig. 4(c))¢ ÚÚ *Ú'b 'ç Cjr º ©j { > ® . º " Ôf 8 ~ º*ö ÷7>Ú ª~~ z²8 ïz ~ º ";öB z²8 ç&'b ¸f 8~ º* *>'b ÿ~V r^ *W 'ç ¶ò~ ãÖ ¢>'b ¾æ¾º *ç . ®ÊÆÎ ï z O»f "*f z²8~ N& ô ¾º æ ¾ '² ¾º æöB z²8 ~² ª ~ê ~º O» >~ ^ÎÖc jVçj Ï ãÖ ö 'ç z Úvò ê ¦ªê ® z Cjê ¦ªê ® . ^ÎÖc jVç Ö" (Fig. 4(d))¢ ÚÚ ê 5 ê "æ æ~ ã. ê& ª«rb, ö 'ç(Fig. 4(a))¾ j Vç Ö"(Fig. 4(b), (c))öBº ¾ ¾æ p~~ NF¾ ¶ÿN~ ãê& ª«~² ¾æ¾º ©j " > ® . V~ 'ç ;z V» «K 'ç ¶ò¢ *> 'b ¢&W ®² æzÊº ©ö j~ ^ÎÖ c jVçf «K æ>~ ;j Û~ F' 'ç ;z& &Ë~ º Ë6 ® . æ ^Î Öc jVçf çê 'ç ¶òöò jî¢ 7?& çê 'ç ¶ò¦V ^¦' ;¢ ºÂ~¶ röê Ï &Ë~ . $ êæf ? Ç CÚ Úê æj Ò~¶ ~¾ Vã æ" z²8 N& ô ¾º ãê¦ ¦ª¾ 'ç V>b F¢ ºÂ~º Ö FÏ~² Ï > ® . jVç ê~ z²8~ æzf ãê *~ æz¢ { V * öBº v &æ O»j Ï~& . Ñ ® êöBº jVç >¯ *ê~ &ç 'ç Ú z²8~ æz¢ rjV *~ N.

(7) . ~\'Á8öÁ²÷L. Fig. 4. The results of homomorphic filtering with respect to IKONOS PAN sub-image. (a) and (b) represent the original image and the result of kernel-based spatial filtering, respectively. A general 3Ü3 sharpening filter was applied for (b). (c) is the result of histogram equalization. (d) shows the effect of homomorphic filtering (γH=2, γL=0.9, c=1 and D0=10). Öj >¯~& . NÖ~ Ö"º Fig. 5ö B ~& . jVç ê~ z²8" ö 'ç z²8 N ~ .& 8j N Ö 'çb *~&º ' ç Ú¦öB ÚvÚ Êb r' vê æ z²8~ æz& æ . 6 îÊ¢ 'Ï 'ç ;z Ö"(Fig. 5(a))öBº ãê¦ ¦ª ô æ~ ®b z²8~ æz ·çö &'F ZÒ~ OËW ¾æ¾º º 6~ 'Ëb 'B. . ®ÊÆÎ ïz Ö"(Fig. 5(b))öBº ãê¦ ¦ª ß® ô æ © jî¢ jv' 'ç * Ú& z²8 æ~&, Cf ïç~ ê ¦ª º ê ~ ÚvÚ ¦ª Cf ïçb æz~B æöB z²8~ æz& rj r > ® . ö j ^ÎÖc jVç Ö"º (Fig. 5(c)) 'çöB *Ú'b z²8 æ © jî¢ ¦ª'b æz~º ßW ®b º ' ç Cö FÒ~² ·Ï . ê~ ãê ¦ª¾ NF " ? ^¦' * ßW æz& v ê ¦ªöB z²8~ æz& ² ¾æ¾º ©b " > ® . v® ê ïç~ N& æöB ¾æ¾ º CÚ ~ ãê¦öB *~~ æz¢ {~V * ~ ãê¦ªj ºÂ ê ö 'ç" jv * Ú ;{ê(overall accuracy)¢ êÖ ~ (Fig. 6). *Ú ;{êº ;{~² ºÂB ãê~ z² >¢ ö 'çöB ãê ºÂB z² > ¾*Ú ê Ö . ®ÊÆÎ ïz O»" ^ÎÖc jVç ~ ãÖ '' 99% ç~ ;{ê¢ >ö. 6 îÊ V>~ jVçj >¯ ãÖöº 93% ;ê v O»ö j j æº pæò ; {ê& ç&'b &~>º *çj { > ®î. . ©f * jV& B ¢~ :f ?. 6~ 7ö 8j Iº ";öB ãê *~~ æz & B ©b 6B . ©f çê 'çj Ï~ ;& * CÚ~ *~¢ ºÂ~¾ 6 ë~º ãÖ ² ^B& F >ê ®rj ~ . j8ç Ï Òf *W 'ç ¶ò¦V ¶ÿb F¢ ºÂ. Fig. 5. Resultant images of image differencing for comparison of image enhancement techniques..

(8) *9'ç5æ>Ò'ç¶ò~^ÎÖcj8çÏ. . ® (Rencz, 1999). V¢B ^ÎÖc jVçj Ï æz& ¦ªf ;z~ -æ pf ¦ªj 6êÎ ãê ¦ª¾ F, $º ç&¢ ;~º Î"' . öBº B *W' ç ¶òf æbÒ ¶òö &~ ^ÎÖc jVç j >¯ Ê ¾Ò Ö"¢ jv ~ .. Fig. 6. Cases of edge detection with several image enhancement schemes. (a) and (b) show the original image and the extracted edge from sharpening image, respectively. (c) is the result of histogram equalization and (d) shows the effect of homomorphic filtering.. ~¾ 7K¾ ¶K öÒ Ö"¢ æz ¶ò ¢ Ï ß ç&(Anomalous zone)¢ d¶ "* Vã 'ç~ z²8j &çb ~ ïç~ N& ô ¾º ¦ªj ;~º jVçj >¯~º ãÖ Ö"~ Cö ôf Ë6j ¢ >. *9'çb¦8 .\` ºÂ ¢>'b 7Á&çê *W'çj Ï~ F ¢ ºÂ~º ãÖöº *¾Ò ";b * jV¢ Ï~º ãÖ& ô . V¢B öº. * jV¢ ÒÏ ãÖf ^ÎÖc jV¢ Ï ãÖ¢ jv~ wÏ ö & Ò6j B ~¶ ~& . ";öB ÒÏB *W 'çf ;öê ;F æ~ LANDSAT 7 ETM+ 'çb *çêº 30m . Þ ¶ÿz F ºÂ V »bº GDPA(Gradient Direction Profile Analysis) O»(Wang et al.,1992; Lee et al., 2003)" ^Fz O»(Zhang and Suen, 1984)j Ï~& . jVç ¾Ò êö ¶ÿz ãêF ºÂ" "* Ç rj B~º ^Fz ";j >¯ Ö", ^ÎÖc jVçj Ï ãÖ * jV¢ ãÖ. ®jº ¦ª~ F~ ºÂ ' F~ ÖW GöB jv' Ö> Ö"¢ º ©b ¾æÒ .. Fig. 7. Comparative results of linear feature extraction without/with homomorphic filtering..

(9) . ~\'Á8öÁ²÷L. Fig. 8. Homomorphic filtered result with respect to surface magnetic data in Jeju island. (a) is the raw image data. (b) shows the enhanced image of actual magnetic data, which were obtained by ground investigation using homomorphic filtering.. æ\>Ò ¶ò~ Ï öBº " *W 'ç¶ò¢ &çb jV ç >¯ Ö"¢ B~ ªC~&b¾ æbÒ v ¶ò¢ 2Nö æ * æ" 'ç ¶ò~ ãÖöê ãêF ;z~ Ï'b *¾Ò ê ^ÎÖc jVçj 'Ï &Ë ©b .çB. . B"ê æöB G; ¶K ¶ò¢ 'çz ©(Fig. 9(a))" ?f 'çö ^ÎÖc jVçj >¯ Ö"(Fig. 9(b))¢ jv ~ . jVç >¯ ê öº ª «{~æ p~ ö 'çöB 'ç ;z ";b ïç &jN& ² ¾æÎj " > ® .. Ö V ^ÎÖc jVçf 'ç¶òö Òö æ~j >¯ ê "2> 'öB "2 Wª >ÒWªf ;z~ &"2 Wªö 'Ëj ~º «Wªf ç&'b £zB *Ú 'çö ² 'Ëj "æ pbB 'ç ;z¢ >¯~V * V» . V»f V~ 'ç ¾Ò ²*ÞÚöB æö~ ®æ pV r^ö öBº .êÖ V>~ w Ï *Îj î BB~ *W 'ç¶ò¢ &çb &æ þ ¢ >¯~& . ^ÎÖc jVç" * 'öB~ 'ç;z V» "~ N6f * 'öB~ 'ç ;z V» f «K &ç 'ç~ *>' ïç N¢ ;~º > ö ^ÎÖc jVç~ ãÖöº "2> 'öB 'çj F'b ; > ® º © . ^ÎÖ c jVçj 'Ï~º ãÖ 'ç Ú CÚ*~ ãê. ~ &j¢ ;z~, ö 'çöB ¾ æ p~ ^¦' æz¢ ; "V r^ö F¢ ºÂ ¾ ãê¦ ;zö Î"'b 'ÏF > ®j © b 'B . Þ ãê ºÂ ê ö 'ç" *Ú ;{ê¢ j v Ö", 6 îÊ ¾Ò Ö" 'çö j~ ^ÎÖc jVç~ Ö" 'ç ¸f ;{ê¢ º ©b ¾æÒ . ®ÊÆÎ ïz V»j 'Ï ãÖöê ¸f ;{ê¢ æò z²8 ã ö ÖJ ®j ãÖ ªÖ B"º j ~ V r^ö «K 'ç~ ßWö V¢ N& ®j > ® . ^ÎÖc jVç~ ¾Ò Ö"öBº ö 'ç¾. 'ç;z O»~ Ö"öBº ¾ ¾æ p~ ~ ^¦' 'ç~ ßW ;& jv' ¾ ¾æ¾ º ·çj . V¢B ^ÎÖc jVçj Ï~ «K æ> j ;b F'b ö~º 'j ;~ * > ® . æ çê 'çöB ¦ z ^& ;¢ ºÂ~¾ êæ " ? Ç CÚ Úê æj r, æbÒ ¶òö 'Ï ãÖ "æ" z²8 N& ô ¾º ãê¦ªj ;z~¾ "æ" 8 ç&¢ djÚº Î"'¢ © . Ëê *W 'ç¶ò¢ Ï~ F¢ ºÂ ~¾ ¶K, 7K" ?f æbÒ öÒ¶ò¦V ßW ;¢ Ò~º ^ÎÖc jVç Î"' b ÏF > ®j ©b V&B .. Ò Ò º "VF¦ öÏöÒVFBBÒë ^¦ "B~ ¢¦ Ö"ª.. ^^ò Jensen, J. R., 1996, Introductory Digital Image Processing: A Remote Sensing Perspective, Prentice Hall, 141-152 p. Lee, K., Yu, Y. C., and Lee, B. G., 2003, Automatic Road Extraction by Gradient Direction Profile Algorithm (GDPA) using High-Resolution Satellite Imagery: Experiment Study, Korean Jour. of Remote Sensing, 19, 393-402. Myler, H. R. and Weeks, A. R., 1993, The Pocket Handbook of Image Processing Algorithms in C, Prentice.

(10) *9'ç5æ>Ò'ç¶ò~^ÎÖcj8çÏ. Hall, 119-121 p. Parker, J. R., 1997, Algorithms for Image processing and Computer Vision, Wiley Computer Publishing, 241-245 p. Rencz, A. N. (Ed), 1999, Remote Sensing for the Earth Sciences, Manual of Remote Sensing Third Edition, John Wiley and Sons Inc, 307-354 p. Gonzalez, R. C. and Woods, R. E., 2002, Digital Image Processing, Prentice Hall, 198-201 p. Wang, J., P. M. Treitz, and P. J. Howarth, 1992. Road Network Detection from SPOT Imagery for Updating Geo-. . graphical Information Systems in the Rural-Urban Fringe, Int. Jour. of Geographical Information Systems, 6(2): 141-157. Wang, J. and Zhang, Q., 2000, Applicability of a Gradient Profile Algorithm for Road Network Extraction-Sensor, Resolution and Background Considerations, Canadian Jour. of Remote Sensing, 26, 428-439. Zhang, T. Y. and Suen, C. Y., 1984, A fast parallel algorithm for thinning digital patterns, Communications of the Association for Computing Machinery, 27, 236-239.. 2004j 11ú 23¢ ö 7> 2005j 1ú 10¢ >;ö 7> 2005j 1ú 17¢ ö j.

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