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neighbor Nearest interpolation Bilinear interpolation p 2.5 0 0 2.5 25 729500.0 5026300.0 5026300 0 ESRI world file par8_ls.lst par8_ls del = -12.421 295.17 276.46 93.121 -82.718 82.543 -0.30455 0.31061 residuals: x y note: these are in image space !!! 1.000000 2.41 -0.19 2.000000 0.95 1.07 3.000000 0.15 1.07 4.000000 -0.09 -0.54 5.000000 -3.39 -0.71 6.000000 0.83 0.53 7.000000 -1.34 -1.36 8.000000 0.48 0.13 image x,y rms ans = 1.6179 0.81306 a0 a1 a2 b0 b1 b2 c1 c2 ans = -12.421 295.17 276.46 ans = 93.121 -82.718 82.543 ans = -0.30455 0.31061 offsets used to reduce coord magnitude Xref = 733.01 Yref = 5022.1 crd1_ref = 447 crd2_ref = 340 format long g par8_ls del = -12.4214409629976 295.171791718904 276.455776688616 93.1212276106465 -82.7175574839763 82.5430904885927 -0.304547917683162 0.310606496419191 residuals: x y note: these are in image space !!! 1.000000 2.41 -0.19 2.000000 0.95 1.07 3.000000 0.15 1.07 4.000000 -0.09 -0.54 5.000000 -3.39 -0.71 6.000000 0.83 0.53 7.000000 -1.34 -1.36 8.000000 0.48 0.13 image x,y rms ans = 1.61794554021788 0.813063179892285 Page 1 par8_ls.lst a0 a1 a2 b0 b1 b2 c1 c2 ans = -12.4214409629976 295.171791718904 ans = 93.1212276106465 -82.7175574839763 ans = -0.304547917683162 0.310606496419191 offsets used to reduce coord magnitude Xref = 733.007 Yref = 5022.107 crd1_ref = 447 crd2_ref = 340 diary off 276.455776688616 82.5430904885927 Page 2 % % % % % % % % % % % % % % % % % % % % % % % % % % par8_ls.m par8_ls.m 16-nov-08 solve 8-parameter problem by least squares modify to allow pflag=1: x,y conventional pflag=2: x,y photoshop pflag=3 l,s data in con2d.dat (control) and mea2d.dat (measurements) transformation from to ground image with residuals in the image system a0 + a1*X + a2*Y x = --------------------1 + c1*X + c2*Y b0 + b1*X + b2*Y y = -------------------1 + c1*X + c2*Y x=[1 X Y 0 0 0 -xX -xY] [ y=[0 0 0 1 X Y -yX -yY] [ [ [ [ [ [ [ a0 a1 a2 b0 b1 b2 c1 c2 ] ] ] ] ] ] ] ] pflag=2; degrad=180/pi; load con2d.dat load mea2d.dat % shift in X&Y only for now % Xref=con2d(1,2); % Yref=con2d(1,3); % let's try ground coords in km Xref=733007/1000; Yref=5022107/1000; crd1_ref=447; crd2_ref=340; [npts,ndum]=size(con2d); xpho=zeros(npts,1); ypho=zeros(npts,1); B=zeros(2*npts,8); f=zeros(2*npts,1); % we fiddle with measurement system coordinates so that the final % image coordinates used in the 8-par have x to the right and y up FY=0; for i=1:npts X=con2d(i,2)/1000 Y=con2d(i,3)/1000 % coordinate 1,2 crd1=mea2d(i,2) crd2=mea2d(i,3) switch pflag case 1 x=crd1; - Xref; - Yref; crd1_ref; crd2_ref; Page 1 par8_ls.m y=crd2; case 2 x=crd1; y= -crd2 case 3 x=crd2; y= -crd1 otherwise end ii=(2*i)-1; B(ii ,:)=[1 B(ii+1,:)=[0 f(ii )=x; f(ii+1)=y; end + FY; + FY; X Y 0 0 0 -x*X -x*Y]; 0 0 1 X Y -y*X -y*Y]; del=inv(B'*B)*B'*f; del a0=del(1); a1=del(2); a2=del(3); b0=del(4); b1=del(5); b2=del(6); c1=del(7); c2=del(8); resid=f - B*del; disp('residuals: x y'); disp('note: these are in image space !!!'); rmsx=0; rmsy=0; for i=1:npts xidx=(i*2)-1; yidx=xidx+1; vx=resid(xidx); vy=resid(yidx); rmsx=rmsx + vx*vx; rmsy=rmsy + vy*vy; fprintf(1,'%5f %10.2f %10.2f\n',i,vx,vy); end rmsx=sqrt(rmsx/npts); rmsy=sqrt(rmsy/npts); disp('image x,y rms'); [rmsx rmsy] disp('a0 a1 a2 b0 b1 b2 c1 c2'); [a0 a1 a2] [b0 b1 b2] [c1 c2] disp('offsets used to reduce coord magnitude'); Xref Yref crd1_ref crd2_ref Page 2
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photo1_08_hw3_sol.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: Nearestneighbor interpolation Bilinearinterpolation p 2.5 0 0 2.5 25 729500.0 5026300.0 5026300 0 ESRIworldfile par8_ls.lst par8_ls del = -12.421 295.17 276.46 93.121 -82.718 82.543 -0.30455 0.31061 residuals: x y note: these are in image space !...
603hw5.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: Homework 5 (Revised 14-April) Select a minimum of 3, from the 6, close-range terrestrial photos of the north end of the chemical engineering building. Select pass-points and control points Measure all image coordinate data Determine initial approxima...
603hw5.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: Homework 5 (Revised 14-April) Select a minimum of 3, from the 6, close-range terrestrial photos of the north end of the chemical engineering building. Select pass-points and control points Measure all image coordinate data Determine initial approxima...
506_03_hw4_sol.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: CE 506 Homework 4 Solution 27 Sept. 2003 Problem 1(a) angle figure, observations only, equal precision Matlab code % hw41a.m ce506 - \'03 % 27-sep-03 % set up the problem % solve by observations only n=8; n0=4; r=4; c=r; l=[73+35/60; 130+55/60; 155+...
506_03_hw4_sol.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: CE 506 Homework 4 Solution 27 Sept. 2003 Problem 1(a) angle figure, observations only, equal precision Matlab code % hw41a.m ce506 - \'03 % 27-sep-03 % set up the problem % solve by observations only n=8; n0=4; r=4; c=r; l=[73+35/60; 130+55/60; 155+...
data1_08_notes09.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: ...
data1_08_notes09.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: ...
exm506_2_3.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: ...
exm506_2_3.pdf
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exm503_2_1.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: ...
exm503_2_1.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: ...
ip.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: Examples of how image intensity statistics lead to an interest point or corner detector Developments attributed to Forstner & Harris The Harris corner detector and the Forstner interest operator both utilize the covariance matrix of the shift terms...
ip.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: Examples of how image intensity statistics lead to an interest point or corner detector Developments attributed to Forstner & Harris The Harris corner detector and the Forstner interest operator both utilize the covariance matrix of the shift terms...
writing.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: Latitude by Carter & Carter Write a 2-3 page essay in which you Summarize the book and your reaction to it Address one of the following 3 questions/issues o In data adjustment we attempt to (a) discover and account for systematic errors in our obse...
writing.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: Latitude by Carter & Carter Write a 2-3 page essay in which you Summarize the book and your reaction to it Address one of the following 3 questions/issues o In data adjustment we attempt to (a) discover and account for systematic errors in our obse...
506hw8sol.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: ...
506hw8sol.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: ...
503_03_hw2.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: Fiducial Coordinates for p17_i.raw (from text CD) (+110.003, -110.012) mm (-109.990, -110.012) mm Note orientation of the axes that will depend on how the film was scanned x The coordinates come from a calibration report Principal point is at the...
503_03_hw2.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: Fiducial Coordinates for p17_i.raw (from text CD) (+110.003, -110.012) mm (-109.990, -110.012) mm Note orientation of the axes that will depend on how the film was scanned x The coordinates come from a calibration report Principal point is at the...
grad590d_07_notes03.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: ...
grad590d_07_notes03.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: ...
grad590f_08_notes22.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: See annotations along with code, made a few revision to actually make it work! recommend also putting semicolons after most statement to prevent their cluttering up the screen with unneeded numeric output puse = [1;4;7]; I found this worked better ...
grad590f_08_notes22.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: See annotations along with code, made a few revision to actually make it work! recommend also putting semicolons after most statement to prevent their cluttering up the screen with unneeded numeric output puse = [1;4;7]; I found this worked better ...
photo1_08_hw1.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: ...
photo1_08_hw1.pdf
Path: Purdue >> C E >> 597z Fall, 2008
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grad590d_07_notes18.pdf
Path: Purdue >> CE >> 597z Fall, 2008
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grad590d_07_notes18.pdf
Path: Purdue >> C E >> 597z Fall, 2008
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ce597z_07_hw3_sol.pdf
Path: Purdue >> CE >> 597z Fall, 2008
Description: trav07a.m % trav07a.m % solve first problem of homework 3, fall-07 x=[3915.74;2873.49;2351.8;3356.20;2197.94]; y=[9228.31;8492.34;6328.2;5824.15;5005.78]; % ef %x(3)=2351.78736373034; %y(3)=6328.2048063928; % br x(3)=2351; y(3)=6328; siga_sec=5; sigd...
ce597z_07_hw3_sol.pdf
Path: Purdue >> C E >> 597z Fall, 2008
Description: trav07a.m % trav07a.m % solve first problem of homework 3, fall-07 x=[3915.74;2873.49;2351.8;3356.20;2197.94]; y=[9228.31;8492.34;6328.2;5824.15;5005.78]; % ef %x(3)=2351.78736373034; %y(3)=6328.2048063928; % br x(3)=2351; y(3)=6328; siga_sec=5; sigd...
vll2.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Alternate Means of Constraining (via knowledge gained from photogrammetry) a Search: Rather than selecting a point in one image and asking the question, where is the corresponding or conjugate point in the second image?, ask the following question: G...
intro3.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Perspective Geometry Parallel lines (in object space) converge to a vanishing point in the perspective image The vanishing points for all horizontal lines are on the horizon There is a common vanishing point for all vertical lines If the image plane ...
nweek.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: ...
main1.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: LEAST SQUARES IMAGE MATCHING for CE604 J. Bethel 14 June 1997 1 Introduction In the conventional approach to least squares image matching, we model the correspondence between two image fragments by a geometric model six parameter transformation an...
res_rec.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Motivation for Rectification, Interpolation & Resampling: We would like to present the building face in a view as if we were looking at it from in front. We want constant scale and angles represented correctly, so we can do simple measurement, design...
503_06_hw5.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Homework 5. TIN Generation and Processing Each individual (not group) take your groups spot elevation data and breakline data and generate a TIN and 0.5m contour data set. (leave group data intact and work in your own folder) Merge these contours wit...
anaglyph.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Anaglyph Gallery Collection of borrowed and locally produced anaglyph stereo pictures Left view displayed with Red, right view displayed with Blue Allows the perception of depth in otherwise flat, 2D images. CE 503 Photogrammetry I CE 503 Photogr...
gal.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: ...
cams2.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: CAMERAS Consumer digital CCD cameras Aerial Cameras Leica RC-30 Zeiss RMK Zeiss RMK in aircraft Vexcel UltraCam Digital (note multiple apertures Lenses for Leica RC-30. Many elements needed to minimize distortion and other aberrations Leica digi...
intp.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: ...
3dgen.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Generation of 3D Models from Stereo-Digitized Vertex Points CE 503 Photogrammetry I Fall 2006, Updated Fall 2007 Roof vertices of Meredith Residence Hall (X-shaped building above) were stereodigitized in Erdas Imagine Stereo Analyst, using the 3D ...
p3blk.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: CE 603 Photogrammetry II Exp 5-12 from Purdue 3cm block CE 603 Photogrammetry II CE 603 Photogrammetry II CE 603 Photogrammetry II CE 603 Photogrammetry II CE 603 Photogrammetry II Wild /Leica RC-30 Fiducial ID CE 603 Photogrammetry II CE 603 ...
503_06_hw1.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: CE 503 Fall 06 Homework 1, assigned Aug 28, Due Sep 6 Find the camera calibration report in the notes page of class website (may 2005 photography description) Measure 2 of the corner fiducial marks on photo 5-13 as (line,sample) careful, photosho...
match.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Matching: Signal & Feature Search Refinement Limited Exhaustive Constrained Unconstrained Least Squares L1 Similarity Metric Cross Correlation Single Point Many Points Space Domain 1D 2D Frequency Domain Cost Function CE 603 Photogrammetry II ...
503_03_hw5.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Homework 5. Stereo 3D Extraction of Buildings From model 3-6, 3-8 in blockfile403.blk Building Names and Assignments Buildings 1 2 3 4 5 6 7 8 9 10 11 12 CA1 CA2 CA3 CA4 CIVL CHME PHYS MSEE ECE ME NWPKG PSHC 13 14 15 16 17 18 19 20 21 22 23 24 PHAR...
chapter3.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: FGDC-STD-007.3-1998 Geospatial Positioning Accuracy Standards Part 3: National Standard for Spatial Data Accuracy Subcommittee for Base Cartographic Data Federal Geographic Data Committee Federal Geographic Data Committee Department of Agriculture...
icr.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Image Coordinate Refinement & Camera Calibration Image (2D) and sensor (3D) coordinate system defined with respect to focal plane, optical axis and reference direction Perspective center z Optical axis Measurement system (row,column) defined with re...
503_04_hw2.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: CE 503 Photogrammetry I Homework 2 Assigned Tuesday 7 September, due Friday, 17 September We want to rectifiy the photograph shown here, and integrate with a coordinate grid and some feature vectors. The product will be in Indiana State Plane West c...
par8.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Eight Parameter Transformation - Ground XY (plane) to image a0 + a1 X + a2Y r= 1 + c1 X + c2Y c= b0 + b1 X + b2Y 1 + c1 X + c2Y Equations for application of the transformation, ground XY to r,c or row, column in the image. To insure numerical stabi...
503_04_hw1.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: CE 503 Photogrammetry I - Homework 1 Assigned Monday, 30 August, due Wednesday, 8 September Intensity Column 108 20 110 21 117 22 130 23 122 24 120 25 14 15 73 80 70 45 50 53 50 74 75 50 60 70 70 75 Column 75 52 90 75 85 90 100 76 80 120 150 120 110...
603intr1.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Index Mosaic of 1999 Purdue Block: 80% Forward Overlap and 60% Side Overlap (usual is 60/30 !) Many trees show that October is not best time. CE 603 Photogrammetry II Spring 2003 Purdue University HYMAP Data, Summer 1999 CE 603 Photogrammetry ...
pur_gcp.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Ground Control Requirements Purdue Site Control Pt Pairs - 9 (one target, one photo id) Project Site Point Descriptions for Purdue/NGA/Surdex Photo Block May, 2004 The points occur in pairs at 9 locations (18 total). We will ca...
ro_pw.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Relative orientation, pairwise rectification (normalization or epipolar resampling), L/R channel separation by anaglyph coding. Conjugate points selected for relative orientation: try for z-range Brute force self-calibration ...
lsm.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Exam Review Exam Friday, 29 march, 3:30 Closed book I will return homeworks on Thursday Some short answer definitions, some problems with computation, (bring calculator) Review everything on the course web page, plus textbook chapters 1,2,3, 4(colli...
shift.pdf
Path: Purdue >> C E >> 503 Fall, 2008
Description: Perspective effects may cause undesirable visual rendering of planar object Recall from perspective, that lines not parallel to the image plane will converge at a vanishing point Architectural photographers encounter this frequently A solution to ...
506stat.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: 95% 95% ...
classex1.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: ...
hw2sol.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: Ce506 homework #2 solution 6-sep-02 Problem 1. minimize f ( x, y ) = 2 x 2 + 3 y 2 subject to y = 2 x + 5 (a) Solution by substitution Extract and solve the matrix equation f ( x) = 2 x 2 + 3(2 x + 5 )2 = 14 x 2 + 60 x + 75 df dx = 28 x + 60 = 0 ...
506hw01.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: ...
506hw6sol.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: ...
hw3sol.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: CE 506 02 Homework #3 Solution, Obs. Only using matrix method Problem 3-9 # 1 2 3 4 obs 30-00-20 50-00-00 20-00-00 40-00-20 Problem 3-10 n=4, n 0=3, r=1 1 cond. eqn. Av = f 10 10 sec v= 10 10 #x y n=5, n 0=2, r=3 3 condition equations 1 ...
hw4sol.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: ...
ex_scrshot.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: ...
nonlinex.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: ...
exm02a.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: ...
506hw5sol.pdf
Path: Purdue >> C E >> 506 Fall, 2008
Description: ...
data1_08_notes04.pdf
Path: Purdue >> C E >> 597 Fall, 2008
Description: ...
data1_08_exam1.pdf
Path: Purdue >> C E >> 597 Fall, 2008
Description: ...
data1_08_notes15.pdf
Path: Purdue >> C E >> 597 Fall, 2008
Description: ...
data1_08_hw1.pdf
Path: Purdue >> C E >> 597 Fall, 2008
Description: Tues. 16 Sept. ...
matrix_resize.pdf
Path: Purdue >> C E >> 597 Fall, 2008
Description: elim_col.m % elim_col.m 8-nov-04 % eliminate a list of columns from a matrix function Bnew = elim_col(B,col_list); [m,n]=size(B); [p,q]=size(col_list); nelim=max([p q]); newcol=n-nelim; if(newcol<1) disp(\'trying to eliminate too many columns\'); pause...
