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imagej-elphel
Commit 91616de2 authored by Andrey Filippov's avatar Andrey Filippov
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trying with actual kernels

parent be7e6c62
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Showing with 508 additions and 217 deletions
src/main/java/EyesisDCT.java
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src/main/java/Eyesis_Correction.java
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src/main/java/FactorConvKernel.java
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......@@ -78,7 +78,7 @@ public class FactorConvKernel {
public double currentRMS ;
public double firstRMS;
public double nextRMS ;
public double [] RMSes = {-1.0,-1.0};
public double currentRMSPure=-1.0; // calculated RMS for the currentVector->currentfX
public double nextRMSPure= -1.0; // calculated RMS for the nextVector->nextfX
public double firstRMSPure= -1.0; // RMS before current series of LMA started
......@@ -98,7 +98,8 @@ public class FactorConvKernel {
public double goal_rms_pure;
public LMAData lMAData = null;
public int numLMARuns = 0;
public int target_window_mode = 2; // 0 - none, 1 - square, 2 - sin
public int target_window_mode = 2; // 0 - none, 1 - square, 2 - sin, 3 - sin^2
public boolean centerWindowToTarget = true; // center convolution weights around target kernel center
public class LMAArrays {
public double [][] jTByJ= null; // jacobian multiplied by Jacobian transposed
......@@ -141,6 +142,7 @@ public class FactorConvKernel {
public double [] saved_rmses = null;
public double [] first_rmses = null;
public int target_window_mode = 2; // 0 - none, 1 - square, 2 - sin
public boolean centerWindowToTarget = true; // center convolution weights around target kernel center
public LMAData(){
......@@ -148,8 +150,9 @@ public class FactorConvKernel {
public LMAData( int debugLevel){
this.debugLevel = debugLevel;
}
public void setTargetWindowMode(int mode){
target_window_mode = mode;
public void setTargetWindowMode(int mode, boolean centerWindowToTarget){
this.target_window_mode = mode;
this.centerWindowToTarget = centerWindowToTarget;
}
public void initLMAData(){
......@@ -390,20 +393,36 @@ public class FactorConvKernel {
System.out.println("getWeight(), delete jacobian");
}
if ((weights[0] == null) || (weights[0].length != target_kernel.length)){
if (debugLevel > 2){
System.out.println("Convolution weight is null/outdated, regenerating default (only center part)");
int xc = 0;
int yc = 0;
int conv_size = asym_size + 2*sym_radius-2;
int cc = conv_size/2;
if (this.centerWindowToTarget) {
double s0=0.0,sx=0.0,sy=0.0;
for (int i = 0; i < conv_size; i++){
for (int j = 0; j < conv_size; j++){
double d = target_kernel[conv_size*i+j];
d *= d;
s0 += d;
sx += d* (j - cc);
sy += d* (i - cc);
}
}
xc = (int) Math.round(sx/s0);
yc = (int) Math.round(sy/s0);
}
double [] sins = new double [2*sym_radius-1];
for (int i = 1; i< 2*sym_radius; i++) sins[i-1] = Math.sin(Math.PI*i/(2.0 * sym_radius));
weights[0] = new double [target_kernel.length];
int conv_size = asym_size + 2*sym_radius-2;
int left_top_margin = ((asym_size-1)/2); // inclusive
int right_bottom_margin = left_top_margin + (2 * sym_radius - 1); // exclusive
int left_margin = ((asym_size-1)/2) +xc; // inclusive
int top_margin = ((asym_size-1)/2) + yc; // inclusive
int right_margin = left_margin + (2 * sym_radius - 1); // exclusive
int bottom_margin = top_margin + (2 * sym_radius - 1); // exclusive
for (int i = 0; i < conv_size; i++) {
for (int j = 0; j < conv_size; j++){
int cindx = i * conv_size + j;
if ((i >= left_top_margin) && (i < right_bottom_margin) && (j >= left_top_margin) && (j < right_bottom_margin)) {
weights[0][cindx] = (target_window_mode>=2)?(sins[i-left_top_margin]*sins[j-left_top_margin]):1.0;
if ((i >= top_margin) && (i < bottom_margin) && (j >= left_margin) && (j < right_margin)) {
weights[0][cindx] = (target_window_mode>=2)?(sins[i-top_margin]*sins[j-left_margin]):1.0;
if (target_window_mode == 3) {
weights[0][cindx]*=weights[0][cindx];
}
......@@ -412,7 +431,9 @@ public class FactorConvKernel {
}
}
}
}
}
// public boolean centerWindowToTarget = true; // center convolution weights around target kernel center
//target_window_mode
rebuildMapsPars(false); // only if it does not exist
double sw = 0.0;
......@@ -749,6 +770,7 @@ public class FactorConvKernel {
} // class LMAData
public FactorConvKernel(){
this.new_mode =true;
}
public FactorConvKernel(boolean new_mode){
......@@ -760,10 +782,19 @@ public class FactorConvKernel {
this.sym_radius = sym_radius;
}
public void setTargetWindowMode(int mode){
public void setTargetWindowMode(int mode, boolean centerWindowToTarget){
target_window_mode = mode;
this.centerWindowToTarget = centerWindowToTarget;
}
public double[] getRMSes(){
return this.RMSes; // lMAData.getRMSes();
}
public double getTargetRMS(){
return lMAData.getTargetRMSW();
}
public double [] generateAsymWeights(
int asym_size,
double scale,
......@@ -844,7 +875,9 @@ public class FactorConvKernel {
lMAData.setSymKernel(null, sym_mask_frozen);
levenbergMarquardt();
lMAData.setSymKernel(null, sym_mask);
return levenbergMarquardt();
boolean OK = levenbergMarquardt();
this.RMSes = lMAData.getRMSes().clone();
return OK;
} else{
initLevenbergMarquardt_old(fact_precision, seed_size, asym_random);
if (mask != null){
......@@ -1116,6 +1149,7 @@ public class FactorConvKernel {
System.out.println();
}
}
this.RMSes = RMSes.clone();
return numAsym;
}
......@@ -2148,16 +2182,7 @@ public class FactorConvKernel {
private void initLevenbergMarquardt(double fact_precision, int seed_size, double asym_random){
lMAData = new LMAData(debugLevel);
lMAData.setTarget(target_kernel);
lMAData.setTargetWindowMode(target_window_mode);
/* double s = 0.0;
for (int i = 0; i<target_kernel.length; i++){
s+= target_kernel[i]*target_kernel[i];
}
this.goal_rms_pure = Math.sqrt(s/target_kernel.length)*fact_precision;
*/
// this.currentVector = setInitialVector(target_kernel, null); // should be (asym_size + 2*sym_radius-1)**2
lMAData.setTargetWindowMode(target_window_mode, centerWindowToTarget);
double [][]kernels = setInitialVector(target_kernel, seed_size, asym_random); // should be (asym_size + 2*sym_radius-1)**2
sym_kernel_scale = kernels[0][0];
for (int i=0;i<kernels[0].length;i++) if (!Double.isNaN(kernels[0][i])) kernels[0][i] /=sym_kernel_scale;
......@@ -2166,12 +2191,8 @@ public class FactorConvKernel {
lMAData.setAsymKernel(kernels[1]);
this.goal_rms_pure = lMAData.getTargetRMSW()*fact_precision;
this.target_rms = lMAData.getTargetRMSW(); //Math.sqrt(s/target_kernel.length);
// lMAData.invalidateLMAArrays(); // should be in each run , not at init
resetLMARuns();
// this.currentVector = setVectorFromKernels(kernels[0], kernels[1]);
}
private boolean levenbergMarquardt(){
long startTime=System.nanoTime();
......
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