International Journal of Scientific & Engineering Research, Volume 6, Issue 11, November ISSN

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1 Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 11, Novmbr Fusion an Application of Digital Procssing using Wavlt Transform Miss. Dvyani P. Dshmukh#1, Prof. A. V. Malviya*2 #M.E. Studnt(Final Yar), Digital Elctronics, Amravati Univrsity, Sipna collg of Enginring and Tchnology, Amravati, Maharashtra, India. *Assistant Profssor, (M.E) Digital Elctronics, Sipna collg of Enginring and Tchnology, Amravati, Maharashtra, India. Abstract- In today s ra digital imag procssing has wid aras of application. On of th most important applications of imag procssing is in imag fusion. fusion is a tchniqu which is usd for combining rlvant information from two or mor imags into a singl imag. This fusd imag contains mor information than any of th two input imags. Th fusd imag can hav complimntary spatial and spctral rsolution charactristics. W can apply this mthod in rmot snsing application as wll as satllit imaging application. In this proposd work, two imags ar fusd basd on th wavlt transform using diffrnt fusion tchniqu. Th objctiv of this Proposd work is to fus two imags in such a way that w can gt bttr rsult which contain mor information. Th rspctd rsults will valuat using paramtrs lik Psudo Signal to Nois Ratio, Root Man Squar Error, Standard Dviation and Entropy. Kywords Fusion, Wavlt Transform, Pak Signal to Nois Ratio, Root Man Squar Error, Standard dviation, Entropy, Spatial rsolution, Spctral rsolution. 1.Introduction fusion tchniqu is vry important in digital imag procssing. In this tchniqu, two imags ar mrg to gt mor and accurat information. In traditional data fusion, data fusion can b dividd into thr lvls ths lvls ar pixl lvl fusion, fatur lvl fusion and dcision lvl fusion. Ths diffrnt fusion lvls hav diffrnt algorithms and hav diffrnt application. Th fusion is a tchniqu is usd for rmot snsing and mapping application. For that purpos diffrnt typs of snsor tchnology is usd. Thr ar diffrnt typs of snsor ar availabl. In many rmot snsing and mapping application th fusion of multispctral and panchromatic imag is vry important issu. In th fild of satllit imag classification th quality of th imag classifir is affctd by th fusd imag quality. For that purpos many imag fusion tchniqus and softwar tools hav bn dvlopd. Th wll-known mthod includ th Brovry, th IHS(Intnsity. Hu, Saturation) colour modl, th PCA (Principal Componnt Analysis) mthod and wavlt basd mthod. fusion is also having an application in satllit imag fusion as wll as in mdical imag fusion.

2 Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 11, Novmbr Figur 1.1 Basic Fusion Schm Abov figur shows th basic imag fusion schm. In this figur imag 1 and imag 2 ar combind to xtract th information btwn thos two imags into a singl imag. This figur consist of th two sction namly that is rdundant information and complimntary information. Th rliability of imag is improvd by rdundant information and th capability of imag is improvd by complimntary information. 2. Rlatd Work Various typs of mthod ar proposd in litratur rviw which ar usd for imag fusion. Navnt kaur, t. al [1] Prsntd Rviw On: Fusion Using Wavlt and Curvlt Transform fusion rfrs to th procss of combining th information from two or mor imags into a singl highly informativ imag. Th rsulting fusd imag contains mor information than th input imags. In this papr, two mdical imags ar fusd basd on th Wavlt Transform (WT) and Curvlt transform using diffrnt fusion tchniqus. Th objctiv of th fusion of an MR imag and CT imag of th sam organ is to obtain a singl imag containing as much information as possibl about that organ for diagnosis. Myungjin Choi, t al. [2] introducd a nw mthod basd on a curvlt transform, which rprsnts dgs bttr than wavlts. Sinc dgs play a fundamntal rol in imag rprsntation, on ffctiv mans to nhanc spatial rsolution is to nhanc th dgs. Th curvlt-basd imag fusion mthod provids richr information in th spatial and spctral domains simultanously. Thy prformd Landsat ETM+ imag fusion and found that th proposd mthod provids optimum fusion rsults. Swta Mhta, t. al. [3] introducd th Curvlt Transform and uss it to fus imags. Th xprimnts show that th mthod could xtract usful information from sourc imags to fusd imags so that clar imags ar obtaind. In this papr w put forward an imag fusion algorithm basd on Wavlt Transform and th Curvlt Transform. Low and high frquncy cofficints ar choosn according to diffrnt frquncy domain aftr Wavlt and th Curvlt Transform. In choosing th low frquncy cofficints, th concpt of local ara varianc was chosn to masuring critria. In choosing th high frquncy cofficints, th window proprty and local charactristics of pixls wr analyzd. Finally, th proposd algorithm in this articl was applid to xprimnts of multifocus imag fusion and complmntary imag fusion. Yufng Zhng, t al.[4] Prsntd Th fusion prformanc of th advancd DWT (adwt) mthod proposd hr was compard with six othr common mthods, and, basd on th four quantitativ masurs, was found to prform th bst whn tstd on th four input imag typs. Sinc th diffrnt imag sourcs usd hr varid with rspct to intnsity, contrast, nois, and intrinsic charactristics, th adwt is a promising imag fusion procdur for inhomognous imagry.

3 Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 11, Novmbr Alparon L., t al.[7] prsntd a novl imag fusion mthod, suitabl for pansharpning of multispctral (MS) bands, basd on multi-rsolution analysis (MRA). Th low-rsolution MS bands ar sharpnd by injcting high-pass dirctional dtails Figur 3.1 Basic Fusion Block xtractd from th highrsolution Diagram panchromatic (Pan) imag by mans of th curvlt transform, which is a non-sparabl MRA, whos basis function ar dirctional Abov figur shows th gnralizd dgs with progrssivly incrasing block diagram of imag fusion tchniqu. rsolution.. Dr.S.S.Bdi, t. al [8] dscribs fusion is a tool that srvs to combin multi snsors imags by using advancd imag procssing tchniqus. Particularly it srvs bst in mdical diagnosis i.. computd fusion is a procss of xtracting th information from two imags into a singl imag. As shown in abov block diagram th first stp is to tak input imag first and input imag scond thn apply wavlt transform to thos imags. Aftr that wavlt cofficint ar gnratd. Th nxt tomography (CT), magntic rsonanc stp is to apply fusion rul to thos imags imag (MRI), scan provids diffrnt typs aftr applying th fusion rul fusd imag is of information, by fusing thm w can gt xtractd. Th proposd work is givn accurat information for bttr clinical blow. diagnosis. Th algorithm proposd by th authors 1. To study th diffrnt tchniqus for has its own pros and cons, with rspct to imag fusion. that w will going to propos fficint 2. To study diffrnt transforms with architctur for imag fusion which will b rspct to imag fusion in digital imag usd in various domain, also th statistical procssing. paramtrs lik pak signal to nois ratio, ntropy, standard dviation and root man squar rror will b valuatd to prov our 3. To dsign imag fusion tchniqus using transform mthod. mthod will b fficint with rspct to othrs proposd mthod. 4. Vrification of rsults basd on dsign tchniqus 3. Systm Architctur Fusion is a mthod whr w 3.1 Introduction to Wavlt Transform add or mrg two imags to acquir usful Wavlt transform is on of th most Information. It is vry usful tchniqu. For fficint tool for imag procssing. In this Fusing s w can us diffrnt proposd work two typs of wavlt transform Tchniqus. Figur blow shows transform ar usd. th block diagram for wavlt transform basd imag fusion Discrt Wavlt Transform.

4 Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 11, Novmbr Stationary Wavlt Transform. Figur Discrt Wavlt Transform Basd Fusion. Abov figur shows th block diagram of discrt wavlt transform basd imag fusion. Th first stp is to tak th two imags that is input imag on and input imag two from th imag databas. Nxt stp is to apply discrt wavlt transform to thos imags. Aftr applying th discrt wavlt transform th wavlt cofficint. Th nxt stp is to apply fusion rul to thos imags. Aftr that invrs wavlt transform is applid to gt th fusd imag. Th discrt wavlt transform (DWT) is an implmntation of th wavlt transform in which discrt st of th wavlt scals and translations obying som dfind ruls. In othr words, this transform dcomposs th signal into mutually orthogonal st of wavlt transform is translation invariant. It wavlts, which is th main diffrnc from dos so by supprssing th down-sampling th continuous wavlt transform (CWT), or its implmntation for th discrt tim sris somtims calld discrt tim continuous wavlt transform(dtcwt). Figur Block diagram of DWT and IDWT Abov block diagram shows th rconstruction procss of invrs discrt wavlt transform from discrt wavlt transform. Whr h(n), g(n), h1(n) and g1(n) can b constructd by using quadratur mirror filtr(qmf)[12]. Figur Stationary Wavlt Transform Basd Fusion. Abov figur shows th block diagram of stationary wavlt transform basd imag fusion. Th first stp is to tak th two imags that is input imag on and input imag two from th imag databas. Nxt stp is to apply stationary wavlt transform to thos imags. Aftr applying th stationary wavlt transform th wavlt cofficint. Th nxt stp is to apply fusion rul to thos imags. Aftr that invrs wavlt transform is applid to gt th fusd imag. Th stationary wavlt transform is vry much similar to discrt wavlt transform only diffrnc is that th procss of down sampling is suprssd that s why stationary stp of th dcimatd algorithm and instad up-sampling th filtrs by insrting zros btwn th filtr cofficints. Algorithms in which th filtr is up-sampld ar calld à trous, maning with hols. As with th dcimatd algorithm, th filtrs ar applid first to th rows and thn to th columns. In this cas, howvr, although th four imags producd (on approximation and thr dtail imags) ar at half th rsolution of th original; thy ar th sam siz as th original imag. Th 2-D SWT dcomposition schm is illustratd in Figur [13].

5 Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 11, Novmbr Figur SWT dcomposition schm[14]. 3.2 PERFORMANCE PARAMETERS In this proposd work rsult ar valuatd by focusing on four prformanc paramtrs that is pak signal to nois ratio(psnr) and root man squar rror(rmse), standard dviation(sd) and ntropy(e). Whr m is th hight of th implying th numbr or pixl rows. n is th width of th imag, implying th numbr of pixl columns. Aij bing th pixl dnsity valus of th input imag. Bij bing th pixl dnsity valus of th fusd imag. To calculat RMSE from MSE w tak squar root of MSE. Root Man squar rror is on of th most commonly usd rror projction mthod whr, th rror valu is th valu diffrnc btwn th input data and th rsultant data[14] Pak Signal to Nois Ratio(PSNR) Th mathmatical rlation for PSNR is givn blow, Entropy Entropy is dfind as amount of information containd in a signal. Shannon PSNR is dfind as log of th ratio btwn was th first prson to introduc ntropy to th squar of th pak valu to th Man quantify th information. Th ntropy of th Squar Error multiplid to th valu 10. This imag can b valuatd as, basically projcts th ratio of th highst possibl valu of th data to th rror obtaind in th data. 5 In our cas, at pixl lvl, th highst possibl valu is 255. i.. Whr G is th numbr of possibl gray in a 8 bit gray scal imag, th maximum lvls, P(di) is probability of occurrnc of a possibl valu is having vry bit as 1 > particular gray lvl di. Entropy can dirctly ; which is qual to 255. Thn th rflct th avrag information contnt of an rror btwn th fusd imag and th input imag. Th maximum valu of ntropy can imag is calculatd as th Man Squar b producd whn ach gray lvl of th Error and th ratio valu is obtaind. If both whol rang has th sam frquncy. If th fusd and th input imags ar idntical, ntropy of fusd imag is highr than parnt thn th MSE valu would b 0. In that cas, imag thn it indicats that th fusd imag th PSNR valu will rmain undfind[14]. contains mor information[14] Standard Dviation Root Man Squar Error To find RMSE w hav to first calculat This mtric is mor fficint in th absnc Man Squar Error(MSE) which is givn by of nois. It masurs th contrast in th th following rlation,

6 Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 11, Novmbr fusd imag. An imag with high contrast would hav a high standard dviation. Whr hi f (i) is th normalizd histogram of th fusd imag If (x,y) and L is numbr of frquncy bins in histogram[15]. 4. Rsult and Discussion 4.1 Introduction In this sction rsult and discussion basd on discrt wavlt transform and stationary wavlt transform ar carrid out. Th flowchart of proposd work is givn blow. As shown in abov flow chart th first stp is to tak th first two imags from th imag databas. Th nxt stp is to apply th wavlt transform to thos imags. In this work thr is two typ of wavlt transform ar studid that is discrt wavlt transform and stationary wavlt transform. Aftr application of wavlt transform wavlt cofficint ar gnratd. Aftr that fusion rul is applid to thos cofficints. Th nxt stp is to apply invrs wavlt Transform to thos cofficint to xtract th original cofficint. At last th fusd imag is obtaind. 4.2 Rsult Basd On Discrt Wavlt Transform-This shows th rsult basd on Discrt wavlt transform and th prformanc paramtrs lik pak signal to nois ratio(psnr), root man squar rror(rmse), standard dviation(sd) and ntropy(e) ar valuatd. Input 1 Input imag Fusd 2 Flowchart Fusion Flowchart

7 Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 11, Novmbr Tabl Fusion Basd on Discrt Wavlt Transform 4.3 Rsult Basd On Stationary Wavlt Transform In this sction th rsult basd on Stationary wavlt transform and th prformanc paramtrs lik pak signal to nois ratio(psnr), root man squar rror(rmse), standard dviation(sd) and ntropy(e) ar valuatd. Input 1 Tabl Fusion Basd on Stationary Wavlt Transform 4.4 Rsult Analysis Rsult Analysis basd on Discrt Wavlt Transform. Discrt Wavlt Transform Nam PSNR MS RMS SD Entrop Input Fusd E E y Tabl Evaluation of Rsult Basd on Discrt Wavlt Transform.

8 Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 11, Novmbr Rsult Analysis basd on Stationary wavlt Transform. Nam Stationary Wavlt Transform SD PSNR MSE RMS E Entrop y transform is mor as compar to th valu of standard dviation by stationary wavlt transform is lss. Th valu of ntropy by discrt wavlt and th valu of ntropy by stationary wavlt transform is nar about sam. So from abov discussion for ovrall tstd imags stationary wavlt transform is bst. REFERENCES [1] Navnt Kaur, Madhu Bahl, Harsimran Kaur, rviw on : Fusion Using Wavlt and Curvlt Transform, (IJCSIT) Intrnational Journal of Computr Scinc and Information Tchnologis, Vol. 5 (2), , [2] Myungjin Choi, Ra Young Kim, Myong-Ryong NAM, and Hong Oh kim, Th Curvlt Transform For Fusion. [3] Swta Mhta, Prof. Bijith Marakarkandy, CT AND MRI Fusion Using Tabl Evaluation of Rsult Basd on Curvlt Transform Issn: Stationary Wavlt Transform. Nov 12 To Oct 13 Volum 02, Issu 02. [4] Yufng Zhng, Edward A. Essock and CONCLUSION Bruc C. Hansn Dpt. of Psychological & In this proposd work imag fusion Brain Scincs, Univrsity of Louisvill, mthod is introducd which is basd on th Louisvill, An Advancd Fusion wavlt transform, which incorporatd th Algorithm Basd on Wavlt Transform statistical paramtrs lik pak signal to Incorporation with PCA and Morphological nois ratio(psnr), root man squar Procssing. rror(rmse), standard dviation(sd) and [5] Chavz Jr, P. S., Sids, S. C. & ntropy ar valuatd to prov our mthod Andrson, J. A. 1991, Comparison of thr will b fficint with rspct to othrs diffrnt mthods to mrg multirsolution proposd mthod. As shown in abov rsult and multispctral data: Landsat TM and for ovrall imags th valu of PSNR by SPOT discrt wavlt transform is lss as panchromatic. Photogrammtric Enginring compar to th valu of PSNR by stationary and Rmot Snsing 57 (3) wavlt transform is mor. Th valu of [6] Aiazzi, B., Alparon, L., Baronti, S. & MSE by discrt wavlt transform is mor Garzlli, A Contxt-drivn fusion of as compar to th valu of MSE by high spatial and spctral rsolution data stationary wavlt transform is lss. basd on ovrsampld multi rsolution Although th valu of RSME by discrt analysis. IEEE wavlt transform is mor as compar to th Transactions on Goscinc and Rmot valu of RMSE by stationary wavlt Snsing 40 (10) transform is lss. Although th valu of [7] Alparon, L., Baronti, S., Garzlli, A. & standard dviation by discrt wavlt Nncini, F. 2004a. A global quality

9 Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 11, Novmbr masurmnt of Pan-sharpnd multispctral imagry. IEEE Goscinc and Rmot Snsing Lttrs 1 (4) [8] Dr.S.S.Bdi1, Mrs.Jyoti Agarwal2, Pankaj Agarwal3 Fusion Tchniqus and Quality Assssmnt Paramtrs for Clinical Diagnosis: A Rviw, Intrnational Journal of Advancd Rsarch in Computr and Communication Enginring Vol. 2, Issu 2, Fbruary 2013 [9] Alparon, L., Baronti, S., Garzlli, S. & Nncini, F. 2004b. Landsat ETM+ and SAR imag fusion basd on gnralizd intnsity modulation. IEEE Transactions on Goscinc and Rmot Snsing 42 (12) [10] T. Ranchin and L. Wald, Fusion of High Spatial and Spctral Rsolution imags: Th ARSIS Concpt and Its Implmntation, Photogrammtric Enginring and Rmot Snsing, vol. 66, 2000, pp [11] L. Wald, T. Ranchin and M. Mangolini, Fusion of Satllit imags of diffrnt spatial rsolution: Assssing th quality of rsulting imags,photogrammtric Enginring and Rmot Snsing, vol. 63, no. 6, 1997, pp [12] Shih-Gu Huang ( 黃世谷 ), Wavlt for Fusion, Graduat Institut of Communication Enginring & Dpartmnt of Elctrical Enginring, National Taiwan Univrsity. [13] Mirajkar Pradnya P., Sachin D. Ruikar Fusion Basd On Stationary Wavlt Transform Elctronics & Tlcommunication Dpt. Sinhgad Acadmy of Engg. Pun. [14] Dr. Pankaj Mohindru, Manindr Singh Gill, Dr. Pooja A Nw Fusion Algorithm Basd on,wavlt Transform and Adaptiv Nuro Fuzzy Logic Approach Intrnational Journal of Advancd Rsarch in Elctrical, Elctronics and Instrumntation Enginring Vol. 3, Issu 8, August. [15] Rohan Ashok Mandhar, Pragati Upadhyay,Sudha Gupta Pixl-Lvl Fusion Using Brovy Transform And Wavlt Transform Intrnational Journal of Advancd Rsarch in Elctrical, Elctronics and Instrumntation Enginring Vol. 2, Issu 6, Jun 2013.