Assessment and Evaluation of Different Data Fusion Techniques

Transcription

1 Assessment and Evaluaton of Dfferent Data Fuson Technques A. K. Helmy*, A. H. Nasr * and Gh. S. El-Taweel ** * Natonal Authorty of Remote Sensng and Space Scences, Caro, Egypt. ** Computer Scence Dept., Faculty of Computers and Informatcs, Suez Canal Unversty, Ismala, Egypt Abstract- Data fuson s a formal framework for combnng and utlzng data orgnatng from dfferent sources. It ams at obtanng nformaton of greater qualty dependng upon the applcaton. There are many data fuson technques that can be used to produce hghresoluton multspectral mages from a hgh-resoluton panchromatc (PAN) mage and low-resoluton multspectral (MS) mages, ncludng but not lmted to, modfed Intensty hue saturaton, Brovey transform, Prncpal component analyss, Multplcatve transform, Wavelet resoluton merge, Hgh-pass flterng, and Ehlers fuson. One of the major problems assocated wth a data fuson technque s how to assess the qualty of the fused (spatally enhanced) MS mages. Ths paper represents a comprehensve analyss and evaluaton of the most commonly used data fuson technques. The performance of each data fuson method s qualtatvely and quanttatvely analyzed. Then, the methods are ranked accordng to the conclusons of the vsual analyss and the results from qualty budgets. An experment based on Quckbrd mages shows that there s nconsstency between dfferent performances measures used to evaluate data fuson technques. Keywords Data fuson, multspectral mages, qualty assessment, evaluaton crtera, Quck-brd mages I-INTRODUCTION Data fuson technques are orgnally devsed to allow ntegraton of dfferent nformaton sources, may take advantages of the complementary spatal/spectral resoluton characterstcs typcal of remote-sensng magery [1]. One of the major applcatons of remotely-sensed data obtaned from earth orbtng satelltes s data fuson because of repettve coverage at short ntervals from dfferent satelltes wth dfferent sensors characterstcs. Data fuson s useful n such dverse applcatons as photo-analyss. Automated tasks, such as feature extracton and segmentaton/ classfcaton, have also been found to beneft from data fuson [2]. There s a defnte need for data fuson whch automatcally enhances both spatal and spectral characterstcs of MS and PAN mages. The concept of data fuson goes back to the 1950 s and 1960 s, wth the search for practcal methods of mergng mages from varous sensors to provde a composte mage whch could be used to better dentfy natural and manmade objects. Terms such as mergng, combnaton, synergy, ntegraton, and several others that express more or less the same concept have snce appeared n the lterature [3]. In the remote sensng communty, the followng defnton has been adopted: Manuscrpt receved February, 2010: Revsed verson receved July, 2010 Ths work was supported by Natonal Authorty of Remote Sensng and Space Scence, Caro, Egypt Data fuson s a formal framework n whch are expressed means and tools for the allance of data orgnatng from dfferent sources. It ams at obtanng nformaton of greater qualty; the exact defnton of greater qualty wll depend upon the applcaton [1]. Many mage fuson methods have been proposed for combnng a hgh resoluton panchromatc mage (HRPI) wth low resoluton multspectral mages (LRMIs). A detaled revew on ths ssue was gven by [4]. Ths paper s structured n fve sectons. The followng secton 2 explans the concept of data fuson technques and ntroduces the mathematcal models of several exstng mage fuson methods. In Secton 3, the performances measures used to quantfy the exstng methods are analyzed. In Secton 4, experments conducted based on quck brd mages are presented wth ther results. Fnally, our conclusons are gven n Secton 5. II-DATA FUSION TECHNIQUES A varety of data fuson technques are devoted to merge MS and PAN mages whch exhbt complementary characterstcs of spatal and spectral resolutons [3].Such an applcaton of data fuson s often called Pan sharpenng. Several researchers have attemptng to use dfferent types of satellte mages to address the data fuson problem. Several procedures of data fuson have been proposed whch could ad n updatng resource nventores. These methods nclude modfed Intensty Hue Saturaton (IHS), Brovey transform (BT), prncpal component analyss (PCA), Multplcatve Transform (MT), Wavelet Resoluton Merge (WRM), Hgh- Pass Flterng (HPF), and Ehlers fuson. Data fuson approaches may be broadly characterzed nto several groups. Schowengerdt classfed them nto spectral doman technques [5], spatal doman technques, and scale space technques. Ranchn and Wald classfed them nto three groups [6]: projecton and substtuton methods, relatve spectral contrbuton methods, and those relevant to the ARSIS ' Ameloraton de la Resoluton Spatale Par Injecton de Structures' concept [7]. It s worth mentonng here that accurate spatal regstraton of the two orgnal mages s essental for most data fuson methods. Ths necesstates the use of geometrc rectfcaton algorthms that regster the mages to each other or to a standard map projecton. Moreover some technques requre a radometrc balance between the two mages. 107

2 1- Modfed HIS IHS can only process three bands at a tme (because of usng the RGB to IHS method). However, the color consstency s so good that ths mplementaton of the approach enables mages wth more than three bands to be merged by runnng multple passes of the algorthm and mergng the resultng layers. For example, you can merge an IKONOS 4,3,2 and an IKONOS 3,2,1, and the tool automatcally layer stacks 4,3,2 from the frst merge wth the 1 from the second to produce a merged mage of all four IKONOS bands DN V 1 V 2 and t PAN = H= tan DN 2 DN 6 DN [ V 2 / V1 ], S = V1 + V 2 The technque works by assessng the spectral overlap between each mult-spectral band and the hgh resoluton panchromatc band and weghtng the merge based on these relatve wavelengths. Therefore, t works best when mergng bands where there s sgnfcant overlap of the wavelengths. As such, t may not produce good results when mergng SAR magery wth optcal magery, the Modfed IHS Method for Fusng Satellte Imagery was proposed by [8]. 2-Brovey Transform t MS 1 t MS 2 t MS 3 It s a smple method for combnng data from dfferent sensors. In ths transform, three bands are used accordng to the followng formula: RF GF BF = PAN I R G B Here, R, G, and B are the pxel values of pxel of each band, RF, GF, and BF are the pxel values of pxel of each band that s obtaned by fuson process, and I = (R + G + B )/3. The Brovey Transform [9],[10] was developed to vsually ncrease contrast n the low and hgh ends of an mage s hstogram (.e., to provde contrast n shadows, water and hgh reflectance areas such as urban features). Consequently, the Brovey Transform should not be used f preservng the orgnal scene radometry s mportant. However, t s good for producng RGB mages wth a hgher degree of contrast n the low and hgh ends of the mage hstogram and for producng vsually appealng mages. Snce the Brovey Transform s ntended to produce RGB mages, only three bands at a tme should be merged from the nput multspectral scene, such as bands 3, 2, 1 from a SPOT or Landsat TM mage or 4, 3, 2 ( 2 ) (1) from a Landsat TM mage. The resultng merged mage should then be dsplayed wth bands 1, 2, 3 to RGB. 3-Prncpal Component Analyss The major goal of ths method s to retan the spectral nformaton of the multspectral mages. Ths algorthm s mathematcally rgorous [11]. It s assumed that: PC-1 contans only overall scene lumnance; all nter-band varaton s contaned n the other PCs, and Scene lumnance n the Short Wave Infra Red (SWIR) bands s dentcal to vsble scene lumnance. Wth the above assumptons, the forward transform nto PCs s made. PC-1 s removed and ts numercal range (mn to max) s determned. The hgh spatal resoluton mage s then remapped so that ts hstogram shape s kept constant, but t s n the same numercal range as PC-1. It s then substtuted for PC-1 and the reverse transform s appled. Ths remappng s done so that the mathematcs of the reverse transform do not dstort the thematc nformaton The (PCA) method s best used n applcatons that requre the orgnal scene radometry (color balance) of the nput multspectral mage to be mantaned as closely as possble n the output fle. As ths method scales the hgh resoluton data set to the same data range as PC-1, before the Inverse Prncpal Component calculaton s appled, the band hstograms of the output fle closely resemble those of the nput multspectral mage. Unfortunately, ths radometrc accuracy comes at the prce of a large computatonal overhead. The (PCA) method s slow and requres the most system resources. Its output fle tends to have the same data range as the nput multspectral fle. 4-Multplcatve Transform Ths method uses a smple multplcatve algorthm: (DN low-resoluton )(DN hgh-resoluton )=DN fused-mage (4) The algorthm s derved from the four component technque of [12]. It s argued that of the four possble arthmetc methods to ncorporate an ntensty mage nto a chromatc mage (addton, subtracton, dvson, and multplcaton), only multplcaton s unlkely to dstort the color. Frst the ntensty component s removed va band ratos, spectral ndces, or PC transform. The result s an ncreased presence of the ntensty component. For many applcatons, ths s desrable. People nvolved n urban or suburban studes, cty (3) 108

3 plannng, and utltes routng often want roads and cultural features (whch tend toward hgh reflecton) to be pronounced n the mage. Ths method s computatonally smple; t s generally the fastest method and requres the least system resources. However, the resultng merged mage does not retan the radometry of the nput multspectral mage. Instead, the ntensty component s ncreased, makng ths technque good for hghlghtng urban features (whch tend to be hgher reflectng components n an mage). 5-Wavelet Resoluton Merge The basc theory of Wavelet Resoluton Merge (WRM) s that an mage can be separated nto varous hgh- and lowfrequency components usng varous hgh- and low-pass flters. The wavelet famly can be thought of as a hgh-pass flter. Thus wavelet-based hgh- and low-frequency mages can be created from any nput mage. By defnton, the low-frequency mage s of lower resoluton and the hgh-frequency mage contans the detal of the mage. Ths process can be repeated recursvely. The created lowfrequency mage could be agan processed wth the kernels to create new mages wth even lower resoluton. Thus, startng wth a 5-meter mage, a 10-meter low-pass mage and the correspondng hgh-pass mage could be created. A second teraton would create a 20-meter low- and, correspondng, hgh-pass mages. A thrd recurson would create a 40-meter low- and, correspondng, hgh-pass mages, etc. Usng wavelets, one can decompose the 5-meter mage through several teratons untl a 40-meter low-pass mage s generated plus all the correspondng hgh-pass mages derved durng the recursve decomposton. Ths 40-meter low-pass mage, derved from the orgnal 5-meter pan mage, can be replaced wth the 40-meter multspectral mage and the whole wavelet decomposton process reversed, usng the hgh-pass mages derved durng the decomposton, to reconstruct a 5-meter resoluton multspectral mage. The approxmaton component of the hgh spectral resoluton mage and the horzontal, vertcal, and dagonal components of the hgh spatal resoluton mage are fused nto a new output mage. If all of the above calculatons are done n a mathematcally rgorously way, one can derve a multspectral mage that has the hgh-pass (hghfrequency) detals from the 5-meter mage [13]-[15] In ths scenaro, t should be noted that the hgh-resoluton mage (panchromatc) s a sngle band and so the substtuton mage, from the multspectral mage, must also be a sngle band. There are tools avalable to compress the multspectral mage nto a sngle band for substtuton usng the IHS transform or PCA transform. Alternately, sngle bands can be processed sequentally. Multsensor mage fuson s a tradeoff between the spectral nformaton from LRMI sensor and the spatal nformaton from an HRPI sensor. Wth the wavelet transform fuson method, t s easy to control ths tradeoff [16]. 6 Hgh-Pass Flterng Improvng wavelet-based Resoluton Merge functonalty led to advancement of the Hgh Pass Flterng (HPF) add-back method to the level at whch t yelds results comparable to redundant wavelets but wth much smaller computaton tme and data space requrements. The general algorthm [17], [18] s; a) The rato between multspectral cell sze to hghresoluton cell sze s calculated for quck brd magery, R=4 b) Then HPF of hgh spatal resoluton mage s derved. Ths operaton produces the HPF mage. A hgh pass convoluton flter kernel (HPK) s created and used to flter the hgh-resoluton nput data. The sze of the HPK s a functon of the relatve nput pxel szes, R. All values of the kernel are set to 1 except the center value. There are three possble values for the kernel center value. The lowest of the three values for each kernel sze s the default. c) Resample the mult-spectral mage to the pxel sze of the hgh-pass mage. The low spatal resoluton mage s resampled to the pxel sze of the hgh resoluton mage usng a blnear algorthm (4 nearest neghbors). The resultng mage wll, therefore, have the same pxel sze as the hgh resoluton mage. d) Add the HPF mage to each mult-spectral band. The value of the weght W appled to the HPF mage, pror to addton to the mult-spectral mage, depends on both R and the standard devatons (SD) of both the HPF mage and mult-spectral band. In addton, the weght s allowed to vary so you can adjust the crspness of the result. The calculaton for each band of the nput mage wll then be: Pxel (out) = [Pxel (n)] + [HPF x W] e) Stretch the new mult-spectral mage to match the mean and standard devaton of the orgnal (nput) mult-spectral mage. 109

4 7-Ehlers Fuson The frst step s to transform the low resoluton multspectral mage nto an Intensty-Hue-Saturaton (IHS) mage workng wth three selected bands (RGB). Next, the panchromatc mage P and the ntensty component I are transformed nto the spectral doman usng a twodmensonal Fast Fourer Transform (FFT). The power spectrum of both mages s used to desgn the approprate low pass flter (LP) for the ntensty component and hgh pass flter (HP) for the hgh resoluton panchromatc mage. Based on the rato of pxel szes between the hgh and low resoluton mages, cut-off frequences for these flters can be establshed [19]. Flterng wll be drectly performed n the frequency doman as t nvolves only multplcatons. An nverse FFT transforms both components back nto the spatal doman. The low pass fltered ntensty (I LP ) and the hgh pass fltered panchromatc band (P HP ) are added and matched to the orgnal ntensty hstogram. At the end, an nverse IHS transform converts the fused mage back nto the RGB doman III- EVALUATION CRITERIA FOR DATA FUSION TECHNIQUES In the precedng secton, the mathematcal models of the seven methods were expressed. The performances of each method wll be assessed by comparson to a reference. Then, the methods wll be ranked accordng to the conclusons of the vsual analyss and the results from qualty budgets. We wll use the consstency property recommend by [20] whch states that any synthetc mage, once degraded to ts orgnal resoluton, should be as close as possble to the orgnal mage. In other words, spatal degradaton of the fused mage should lead to the orgnal mage or close. Consstency, however, s a necessary condton, and ts fulfllment does not mply a correct fuson. Many of the methods tested durng ths contest use mult-scale approaches n order to nject hgh spatal frequency components whle preservng low spatal frequency components. Fuson methods adoptng such approaches usually check ths property [7]. When reference MS mages are avalable for comparsons wth fuson results, assessment of fdelty to the reference usually requres computaton of a number of dfferent ndces as ndcated below. 3- Root Mean Square Error (RMSE) The comparson s also made on the bass of the mean squared error (MSE) between the true MS mages and the fused mages. RMSE= Where n and m are number of pxels, f represents the true MS mage ntensty value at the th pxel and f ' s the correspondng fused MS mage ntensty. 4- Average angle error ( f f Gven two spectral vectors v and v f, both havng L components, n whch v = {v 1, v 2,..., v L } s the orgnal spectral pxel vector, whle v f = { v1, v2,..., v L } s the dstorted vector obtaned by applyng fuson to the coarser resoluton MS data, the Spectral Angle Mapper (SAM) denotes the absolute value of the spectral angle between the two vectors. A value of SAM (1) equal to zero denotes absence of spectral dstorton, but radometrc dstorton s possble (the two pxel vectors are parallel but have dfferent lengths). SAM s measured n ether degrees or radans and s usually averaged over the whole mage to yeld a global measurement of spectral dstorton. 5- Relatve dmensonless global error n synthess (ERGAS) Error ndex offers a global pcture of the qualty of the fused product. Ths s gven by: L d h 1 rmse( l) ERGAS = 100 d l L l= 1 µ ( l) ) 1- Average Correlaton Coeffcents (CC) d h /d l s the rato between the pxel szes of Pan and MS, e.g., 1/4 for Ikonos and QuckBrd data. The correlaton between each band of the fused mage and µ(l) s the mean (average) of the l th band, reference MS mages s calculated. Lower value of correlaton L s the number of bands. ndcates hgher spectral dstorton and vce versa. The deal value of ERGAS s zero. = SAM ( v, v) mn ' ) 2 ( v, v) arccos( v. v 2 (5) (6) ( 7) 2- Bas n the Mean and standard devaton The bas between fused and MS mage ndcate the amount of devaton of the fused mage. 6- Qualty ndex Q4 Q4 [21], [22] s obtaned through the use of correlaton coeffcent CC between hyper-complex numbers, quaternon, representng spectral pxel vectors. Q4 s made of three dfferent factors: The frst s the modulus of the hyper- 110

5 complex CC between the two spectral pxel vectors and s senstve to both the loss of correlaton and to spectral dstorton between the two MS data sets. The second and thrd terms, respectvely, measure contrast changes and mean bas on all bands smultaneously. The modulus of the hyper-complex CC measures the algnment of the spectral vectors. Therefore, ts low value may be detected when radometrc dstorton s accompaned by spectral dstorton. Thus, both radometrc and spectral dstortons may be encapsulated n a unque parameter. All statstcs are calculated as averages on N N blocks, ether N = 16 or N = 32. Eventually, Q4 s averaged over the whole mage to yeld the global score ndex. The hghest value of Q4, attaned f and only f the test MS mage s equal to the reference, s one; the lowest value s zero. color and the NIR red green combnaton for false color. The resoluton rato between the Quck-brd HRPI and the LRMIs s 1: 4. Therefore, n the HPF resoluton merge a 5 X 5 boxcar flter was used. The fused results of the PCA, Multplcatve, Brovey, Modfed HIS, HPF, WRM, and Ehlers methods are dsplayed n Fgs. 3 9, respectvely. Snce the results are too large to be assessed together, for better evaluaton, Fg. 10 shows subscenes from the orgnal natural color composte and the correspondng results together. The performance of each fuson method should be evaluated n terms of the qualty of the degraded fused mage compared wth the orgnal LRMIs. It should be as dentcal as possble. IV- EXPERIMENTAL RESULTS AND EVALUATIONS In order to valdate the theoretcal analyss, the performance of the representatve methods dscussed above was further evaluated by expermentaton. A quck-brd panchromatc mage HRPI ( nm) of 0.7-m resoluton and the red ( nm), green ( nm), blue ( nm) and NIR ( nm) bands of the 2.8-m resoluton LRMIs were used n ths experment. The mages cover the area of the pyramd, Caro, Egypt acqured on The par of mages was geometrcally regstered to each other after beng resampled to 0.7 m resoluton usng cubc convoluton technque. Quck-brd data was collected at 11 bts per pxel (2048 gray tones). Ths means that there s more defnton n the gray scale values and the vewer can see more detal n the mage. In order to beneft from ths addtonal nformaton, the processng and evaluaton were entrely based on the orgnal 11-bt data and the data was converted to eght-bt for dsplay purposes only. Fg. 1 shows the HRPI. and the natural color mage of the orgnal LRMIs (red green blue combnaton) s shown n Fg. 2. The NIR band s not shown but was processed and numercally evaluated as well. The study area s composed of varous features such as cars, buldngs, trees, lawn, etc., rangng n sze from less than 1 m up to 100 m. It s obvous that the HRPI has better spatal resoluton than the LRMIs and more detal can be seen from the HRPI. Table-3 gves the correlaton coeffcents (CCs) between the HRPI (downsampled to 2.8-m pxel sze) and the orgnal LRMIs, whch show that the CC of the NIR band s comparable wth the CCs of other bands, ndcatng that the Quck-brd NIR band s very mportant to the Quck-brd PAN band as the other bands. Fg. 1. Orgnal HRPI (panchromatc band). Table 3. Correlaton Coeffcents for the Quck-Brd HRPI (Resampled at 4-m Pxel Sze) and the Orgnal LRMIS red green blue NIR Fg. 2. Orgnal LRMIs (RGB) The modfed IHS and Brovey Transform methods can only handle three bands. In order to evaluate the NIR band as well, we selected the red green blue combnaton for true natural 111

6 Fg. 3. Result of the PCA Method. Fg. 4. Result of the Multplcatve Method Fg. 5. Result of the Brovey Method Fg. 6. Result of the modfed IHS Fg. 7. Result of the HPF Method Fg. 8 Result of WRM Method Fg. 9. Result of Ehlers Method. 112

7 Fg. 10. Subscenes of the orgnal LRMIs, HRPI and the fused resultng HRMIs by dfferent methods (double zoom). (Left to rght sequence, row by row). Orgnal LRMIs, Orgnal HRPI, PCA, Multplcatve, Brovey, HIS, HPF, WRM, and Ehlers. Vsual nspecton provdes an overall mpresson of the detaled nformaton and the smlarty of the orgnal and resultant mages. Comparng the spatal qualty of all the resultant mages (Fgs. 3 9) wth that of the orgnal mages (Fgs. 1-2) vsually, t s obvous that the spatal resolutons of the resultant mages are hgher than that of the orgnal mages. Some small features such as buldng edges, whch were not nterpretable n the orgnal mage, can be dentfed ndvdually n each of the resultant mages. Trees and buldngs are much sharper n the resultant mages than n the orgnal mages. It s easy to see ths effect n Fg. 10. Ths means that all of the used methods can mprove spatal qualty va the fuson process. In fgures 4 and 6 multplcatve and HIS methods produce a sgnfcant color dstorton wth respect to the orgnal LRMSI. In Fg. 3 the PCA methods produce notceable color dstorton wth respect to the orgnal mage, however t looks better. In Fgs. 7 and 8, the HPF and WRM methods produce color dstorton n nstances such as water bodes and vegetated areas. In Fg. 7, the HPF method also exhbts slght color dstorton, as n the brght bult up area, for nstance, but better than WRM methods (see also Fg. 10). Ths may be due to the large rpple outsde ts band-pass n the frequency response of ts low-pass flter. Nevertheless the Ehlers method looks better than all of the other methods n terms of the qualty of spectral nformaton. The HPF and WRM methods look sharper than the others. However, ths s probably due to over-enhancement along the edge area because these addtve methods have not consdered the dfferences n hgh-frequency nformaton between the panchromatc band and the multspectral bands, so ths should not be consdered as a mert of the HPF and WRM methods. The qualty of spectral nformaton s the prncpal crteron. In Fg. 10, t can be seen that the Ehlers method also gves better spatal qualty than the HPF method. Overall, t s obvous by vsual nspecton that the Ehlers method gves the syntheszed result closest to what the correspondng mult sensors would observe at the hgh-resoluton level. In addton to the vsual analyss, the performance of each method was further quanttatvely analyzed by checkng the (next or followng) seven propertes. The correlaton coeffcent (CC), bas n mean, bas n standard devaton, Root mean squared error (RMSE) between the orgnal MS mages and the fused mages, SAM, ERGAS, and Q4. ERGAS and Q4 ndcate the evdence of qualty n terms of spatal detals, whle the RMSE, SAM, bas n mean, bas n standard devaton and correlaton values reflect the fdelty 113

8 of spectral nformaton. For example, the RMSE, bas n mean, SAM, and ERGAS should be as low as possble. On the contrary, the hgher the correlaton coeffcent and Q4 are, the better the fuson s. The obtaned results are summarzed n Table 4. Table 4. Quanttatve Assessment of the Fuson Results Provded By the Consdered Technques Appled To the Quck Brd Data Set: (A) Band 2, (B) Band 3, (C) Band 4 (The IHS and BT Technques Have Been Appled To Bands 2, 3, and 4 False-Color Compostons) CC Mean standard RMSE SAM ERGAS Q4 bas devaton (bas) PCA Multplc B. T HIS HPF WRM Ehlers As can be observed from the table, the measures used to evaluate data fuson technques can be dvded nto two groups, group ndcate the spectral characterstcs of fused mage ncludng CC, bas n mean, bas n standard devaton, RMSE, and SAM. The other one measure the spatal characterstcs ncludng ERGAS and Q4. Frstly regardless of spectral evaluaton, as correlaton coeffcents between orgnal LRMIs and fused mages go hgh, t s an ndcaton that the fused mage exhbts same spectral characterstcs as orgnal mage. It s clear that Ehlers followed by WRM have the hghest correlaton values. On the other hand HPF shows smallest shft, bas n mean, between orgnal and fused mages dstrbuton followed by PCA. Whle Wavelet Resoluton Merge ntroduces the best curve fttng, standard devaton bas, between the two dstrbutons of orgnal and fused mages, also t provdes the best value of RMSE. SAM whch ndcate the absence of spectral dstorton, PCA comes wth the best value followed by HIS As can be seen from the results of spectral evaluaton usng the prevous measures, there s a conflct between the measures, ths s due to the followng: Bas n mean and stander devaton gve an over all magery of the dstrbuton between orgnal and fused mages, dstorton of fused mage s not notceable due to engage n recreaton of these measures. CC s nsenstve to a constant gan and bas between two mages and does not allow subtle dscrmnaton of possble fuson artfacts. SAM wth value of zero, denotes absence of spectral dstorton, but radometrc dstorton s possble (the two pxel vectors are parallel but have dfferent lengths). Secondly regardless of spatal evaluaton, ERGAS measure shows that Ehlers s the best followed by HPF and WRM whle Q4 ntroduce HIS as the best one followed by HPF. Agan there s a conflct between whch technque s the best. The reason of ths conflct due to: ERGAS offers a global pcture of the qualty of the fused product. It depends upon mean and RMSE of each band whch ntroduce vagueness ndcatons. Although Q4 measures the algnment of the spectral vectors (ts good when radometrc dstorton s accompaned by spectral dstorton). All statstcs are calculated as averages on N N blocks. Eventually, Q4 s averaged over the whole mage to yeld the global score ndex. Ths average process may ntroduce uncertanty results. CONCLUSION The performance of many exstng mage fuson technques ncludng, modfed Intensty Hue Saturaton (IHS), Brovey Transform (BT), Prncpal Component Analyss (PCA), Multplcatve Transform (MT), Wavelet Resoluton Merge (WRM), Hgh-Pass Flterng (HPF), and Ehlers fuson, are assessed and evaluated. Vsual and objectve performance evaluatons of the used technques have been conducted usng Quckbrd data. Both spectral and spatal qualtes of the fused products were assessed. It can be concluded that; From expermental results, by combnaton of the vsual nspecton results and the quanttatve results, t s possble to see that there s nconsstency between the dfferent used measures. The vsual analyss has been confrmed by the quanttatve evaluaton. REFERENCES [1] Wald, L. Some terms of reference n data fuson, IEEE Trans. Geosc. Remote Sens., vol. 37, no. 3, pp ,1999. [2] Bruzzone, L., L. Carln, L. Alparone, S. Baront, A. Garzell, and F. 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