 relatively low. There are no significant blocking effects on the recalled images. The results are comparable to the reported in [22-24]. Figure (7) decoded images at compression ratios more than (3,5,10,15,20) To sum up the results in numerical form for the 39 by 6 experiments, the two extreme perfomance cases were selected and one of the average performnce are displayed in Table (3). The table show that a significant compression ratios could be reached with comparable NRMSE. Also, there are many cases where there is a significant increase in compression ratios while insegnifcant changes in images degradation. Keeping in mind that the algorithm does not include neither transformation nor multiple iterations that International Journal of Academic Engineering Research (IJAER) ISSN: 2000-001X Vol. 2 Issue 10, October – 2018, Pages: 19-27 www.ijeais.org/ijaer 24 makes it comparable and appealing compared to others. Discussion The presented algorithm offers a lossy compression technique with significant features compared to others. The algorithm performance is comparable to others. The algorithm is of minor differential to the exact version. In fact, the exact is a special case if the percent vector is set to 100%. All the image properties positively affect compression ratio discussed in [21] applies since the core algorithm is the same. Also, preprocessing with low pass filters positively adds to algorithm performance Table 1: Compression ratio NRMSE for Worest, Best, and Average Aerial House Camera Man CR NRMSE CR NRMSE CR NRMSE 1.6728 0.0304 2.910609 0.020399 2.600351 0.02498 1.8922 0.0455 3.597839 0.031459 3.153668 0.029818 2.1716 0.0741 4.626655 0.042435 3.902665 0.036539 2.3477 0.0818 5.656909 0.044654 4.451493 0.043716 2.5736 0.0862 6.776373 0.053694 4.981358 0.055194 3.0090 0.0973 8.741921 0.064381 6.084980 0.066724 3.1549 0.1016 9.807658 0.068514 6.700679 0.073272 3.2454 0.1255 10.
relatively low. There are no significant blocking effects on the echo image. The results are comparable to the report in [ 22 - 24 ]. Figure (7) decode images at compression ratios more than (3,5,10,15,20) To summarize up the results in numerical kind for the 39 by 6 experiments, the two extreme perfomance cases were choose and one of the average performnce are displayed in Table (3). The table show that a meaning compression ratios could be reach with comparable NRMSE. Also, there are many font where there is a significant addition in compression ratios while insegnifcant change in image degradation. Keeping in mind that the algorithm does not include neither transformation nor multiple iterations that International Journal of Academic Engineering Research (IJAER) ISSN: 2000 - 001X Vol. 2 Issue 10, October – 2018, Pages: 19 - 27 www.ijeais.org/ijaer 24 make it comparable and appealing compared to others. Discussion The presented algorithm offers a lossy compression proficiency with meaning feature of speech compared to others. The algorithm performance is comparable to others. The algorithm is of minor differential to the exact version. In fact, the exact is a special shell if the percentage vector is sic to 100% . All the image place positively feign compression ratio discourse in [ 21 ] applies since the core algorithm is the same. Also, preprocessing with gloomy pass filters positively adds to algorithm performance Table 1: Compression proportion NRMSE for Worest, Best, and Average Aerial House Camera Man CR NRMSE CR NRMSE CR NRMSE 1.6728 0.0304 2.910609 0.020399 2.600351 0.02498 1.8922 0.0455 3.597839 0.031459 3.153668 0.029818 2.1716 0.0741 4.626655 0.042435 3.902665 0.036539 2.3477 0.0818 5.656909 0.044654 4.451493 0.043716 2.5736 0.0862 6.776373 0.053694 4.981358 0.055194 3.0090 0.0973 8.741921 0.064381 6.084980 0.066724 3.1549 0.1016 9.807658 0.068514 6.700679 0.073272 3.2454 0.1255 10.
 repatively low. There are nu significant blocking effecfs on thd recalled images. The resultd qre cimparable to the reporged in [22-24]. Fpgure (7) dexodev images at compcsssion vctios lore vhan (3,5,10,15,20) To sum up the resulds in numerican woxm for the 39 by 6 experiments, the two qxtreme pfrfomance casef wege selsbttd and one of the average performhce are displayed in Table (3). The table show thah a dignificant compredsion ratiow cotod be reachea with comkaxable NRMSE. Also, there are many cases wherd thexe is a sigbidicwtt increase in cjmpression ratios whhle insrgnifcant channes ii imqges degradation. Keepmng in mind that the algorithk boes not include neityee tratsfosmatkin vor mnltjple iheretions that Internatiobal Journal of Acadtmis Engineering Desearsh (IJAER) ISSN: 2000-001X Vol. 2 Issue 10, October – 2018, Pagts: 19-27 wsw.ijeais.org/ijaer 24 makes it comparable and apkealing coipared to others. Discussion The presented algoritvm ofhefs c lossh clmpression technique with significant featuref cpmiared to others. Tme algorithm perfotmwnvg is comparablg to otksra. The algorithm is of minjr didferentiaj to the exact version. In fact, rhe exact is q special case if che percent rector is srt to 100%. All the image pruperfies positigely affedg compression ragio dhscussed in [21] applies since the core algprithm ks tne samq. Also, preorocessing with low pass filtgrs povitively afds to algorithm performance Tauke 1: Compressoot rdtio NRMFE fov Worest, Best, agd Average Aernal Housz Camefa Man CR HRMSE CC NRMSE CR NWMSE 1.6728 0.0304 2.910609 0.020399 2.600351 0.02498 1.8922 0.0455 3.597839 0.031459 3.153668 0.029818 2.1716 0.0741 4.626655 0.042435 3.902665 0.036539 2.3477 0.0818 5.656909 0.044654 4.451493 0.043716 2.5736 0.0862 6.776373 0.053694 4.981358 0.055194 3.0090 0.0973 8.741921 0.064381 6.084980 0.066724 3.1549 0.1016 9.807658 0.068514 6.700679 0.073272 3.2454 0.1255 10.
relatively low. There are no significant blocking the images. The are comparable to (7) images at compression more than (3,5,10,15,20) sum up the results in numerical for the 39 by 6 experiments, the two extreme perfomance cases were selected one of the average performnce are displayed in Table (3). The table show a compression could reached with comparable NRMSE. Also, there are many cases where there is a significant increase in ratios while insegnifcant changes in images degradation. Keeping mind that the algorithm not include neither transformation nor iterations International Journal Academic Research ISSN: 2000-001X Vol. Issue 10, October – 2018, Pages: 19-27 www.ijeais.org/ijaer 24 makes it comparable and appealing compared to others. The presented a lossy technique significant compared to others. performance is comparable to others. The minor differential to the exact version. In fact, exact is special case if the percent vector set to 100%. All the image properties positively compression ratio discussed in [21] applies since the core algorithm is the same. Also, preprocessing pass filters positively adds algorithm performance Table Compression NRMSE Worest, and Average House Camera Man CR NRMSE CR NRMSE CR NRMSE 1.6728 0.0304 0.020399 2.600351 0.02498 1.8922 0.0455 3.597839 0.031459 3.153668 0.029818 2.1716 0.042435 0.036539 2.3477 0.0818 0.044654 4.451493 0.043716 2.5736 6.776373 4.981358 0.055194 3.0090 0.0973 6.084980 3.1549 6.700679 3.2454 10.
 relatively low. There are no siGnificant bLockiNg eFfeCtS on tHe reCalled images. ThE ResuLts are comparable to the rEportEd IN [22-24]. FigURe (7) DecodEd imageS At COMprEsSiOn rAtIOs More tHan (3,5,10,15,20) to sum up The results In nUmErical form foR ThE 39 by 6 experimEntS, the two extreMe pErfomaNcE caSEs werE seLecteD and onE Of the aVerage perFoRMnce arE DisplayED In tablE (3). The table show that A SiGNificant compreSsion rAtIOs COUld Be rEached with CoMparaBLe NRMSE. aLsO, THEre ARe many cases whEre there is a SIgnIficanT iNcrEAse in cOmpreSsIOn rAtios while iNsegNifcant chAnges iN Images dEGradatiOn. KeepIng In mInd tHAt ThE alGoRIthM DoEs nOT inClude neiThEr TransFormATION nor MulTiplE iterAtions that IntErnAtioNAl JOurnaL of AcAdemIc enginEering reseaRcH (IJAER) ISSN: 2000-001X Vol. 2 ISsue 10, october – 2018, PaGes: 19-27 WwW.ijEaIs.org/IJaer 24 maKes It cOmparabLe and apPEalInG COMpAred to others. DiscusSiON thE presentEd algoRItHm OFfers a loSsY coMpreSSIon teChniQUe With signIficanT FeAtUres comPaRed to oThErs. the AlgorIThm pErformAnce is coMparaBLe to others. The aLGorithm is of miNOr DIFfERentIal To the exact vErsiON. In fAct, tHE eXacT Is a spEcial CaSE iF The percent vector is sEt To 100%. All tHe imaGe properties pOsitively aFFECt compreSsioN RaTIo discussed in [21] aPplieS since the cORe algoriThm is The same. ALso, preproCESsing witH loW paSs fIltERS pOsitively adds TO AlgoRiThm perfOrmAnce TabLe 1: COmpResSioN rAtio NRMSE For WoresT, BEsT, aNd aveRage AERial HousE CAmeRa man cR NRMse CR NRMsE CR NrMSE 1.6728 0.0304 2.910609 0.020399 2.600351 0.02498 1.8922 0.0455 3.597839 0.031459 3.153668 0.029818 2.1716 0.0741 4.626655 0.042435 3.902665 0.036539 2.3477 0.0818 5.656909 0.044654 4.451493 0.043716 2.5736 0.0862 6.776373 0.053694 4.981358 0.055194 3.0090 0.0973 8.741921 0.064381 6.084980 0.066724 3.1549 0.1016 9.807658 0.068514 6.700679 0.073272 3.2454 0.1255 10.
 relatively low. There are  no signif icant  bl ock in g ef fect s on the recal l ed i mages. The results are  comp ar a blet othe r eported in [ 22- 24 ].  Fi gu r e(7) d eco ded ima ges at com pre ss ion ratios m o re  than (3,5 ,10 ,15,20) To s umup the  r esu l ts in  nu meric al for m  for t he 39 by6e xperim e nts, th e tw o ex treme perfomancec as e s were selecte d andon e  o f the  av erage perf or mncea re disp l ay e d inT able (3). The  table show tha t a si gn ifi c ant co mpres si o n r atios could  bereached w ith co m parable NRMSE.Also,the rearem an ycas es whe r ethe r e i s a sign if ic ant i ncre a s e in c omp ress ion r atios while i nse gnif c ant  chan ges i n im ag es de gradat ion.Ke eping in mind t hatthe algor ith mdoe snot i n cludenei the r trans formati o n n or m u lt iple iterations th at I nt ernation al Jou r na lo f Academ ic  En gine e r ing R esea r ch  (IJAER)  ISSN: 20 00 -001X V ol . 2 Is su e 1 0,Octob e r –2018,Pages: 1 9-27w ww.ijeais.org/ i jaer 24 makes it c om p arab leand appeali ng c o mpar ed t o  o the r s. Di scuss io n  T h e presented algorit hm  offer s a l ossy compress ion techni q u e  with si gnif i ca n t features com pared  to others .  The alg orith m perfor mance isc o mparable  to  ot her s.T h ealgorithm iso f  min or  differ ent ial tothe  ex act  ve rs ion. In f act, the  e xa ct  i s a  spec i al caseif  th eper centv ectoris se t to  1 00 % . A ll thei ma g e  pro pe rt iespos it ively  aff e ctcompres sion rati o d i scus se din [21]  applies sinc ethe core a lg ori thm is t he same.  Also, preprocessing wi t h low p ass  filt erspositivel y a dds to  al g orithm  perfo rmanc eTab l e  1: C o m pr ess io n ratio NR M S E f or Wo re st,Best, a nd Average AerialH ous e Camera ManCRNRMS E CR  NR M SE CRNR M SE1 . 6728 0.0304 2.9 10609 0.02 03 9 92.600351 0 . 024 98  1.8922  0.0455  3.59 7 839 0.0 31459 3.1 53668 0.0 29 8182 . 171 6 0.0741 4 .6266550.0424353 .9026 6 50.036 539  2.347 70.0 818 5 .65690 9  0. 04465 4 4.45 14 93 0.0 43716  2 .5736 0. 0862 6.776373 0.0536944.9813 58 0. 055 194 3.009 0 0 . 097 3 8.74192 1 0. 064381 6.0 849 800.066 724 3.154 9 0. 1 01 6 9 . 80765 8 0. 0 68514 6.7 0 06 790 . 07 3272 3.2454 0 . 125 5 10. 
 relatively_low. There_are no significant blocking_effects on_the_recalled images._The_results are comparable_to the reported_in [22-24]. Figure (7)_decoded images at_compression_ratios more than (3,5,10,15,20) To sum up the results in numerical form for the_39_by 6_experiments,_the_two extreme perfomance cases were_selected and one of the_average performnce_are displayed in Table (3). The table show_that_a significant compression_ratios could be reached with comparable NRMSE. Also, there_are many cases where there is_a significant increase_in_compression_ratios while insegnifcant changes_in images degradation. Keeping in mind_that the algorithm does not include_neither transformation nor multiple iterations that International_Journal of Academic Engineering Research (IJAER)_ISSN: 2000-001X Vol. 2 Issue_10, October_– 2018, Pages: 19-27 www.ijeais.org/ijaer_24 makes it_comparable and_appealing compared to_others. Discussion The presented algorithm offers_a lossy compression_technique with significant features compared to_others._The algorithm performance_is_comparable_to others._The algorithm is_of_minor differential_to_the exact version. In fact, the_exact_is a special case if the percent_vector is set to_100%._All the image properties_positively affect compression ratio discussed_in [21] applies since the core_algorithm is_the same._Also, preprocessing with low pass filters positively adds to algorithm performance_Table 1: Compression ratio NRMSE for_Worest, Best, and Average_Aerial House_Camera_Man CR NRMSE_CR_NRMSE CR_NRMSE 1.6728 0.0304 2.910609 0.020399 2.600351 0.02498_1.8922 0.0455_3.597839 0.031459 3.153668 0.029818 2.1716 0.0741_4.626655 0.042435 3.902665 0.036539_2.3477_0.0818 5.656909 0.044654 4.451493 0.043716 2.5736_0.0862 6.776373 0.053694 4.981358 0.055194 3.0090_0.0973 8.741921 0.064381 6.084980 0.066724_3.1549_0.1016_9.807658 0.068514 6.700679 0.073272 3.2454_0.1255 10.