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Commit 8ad607c6 authored by Andrey Filippov's avatar Andrey Filippov
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working on motion vectors strength equalization

parent ad8191c2
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Showing with 606 additions and 19 deletions
src/main/java/com/elphel/imagej/tileprocessor/ImageDtt.java
View file @ 8ad607c6
......@@ -2802,6 +2802,19 @@ public class ImageDtt extends ImageDttCPU {
}
if (half_disparity > 0.0) { // scale by disparity
mv[nTile][2] *= half_disparity/(half_disparity + pxd[nTile][2]);
// } else { // temporary, testing, make equalization?
// double disp0 = 5.0;
// if (pxd[nTile][2] > disp0) {
// mv[nTile][2] *= pxd[nTile][2]/disp0;
// }
/*
} else {
double disp0 = 5.0;
if (pxd[nTile][2] > disp0) {
mv[nTile][2] *= 10; // pxd[nTile][2]/disp0;
}
*/
}
if ((half_avg_diff > 0.0) &&(num_neibs > 0)) {
double dx = mv[nTile][0] - sx / num_neibs;
......
src/main/java/com/elphel/imagej/tileprocessor/IntersceneMatchParameters.java
View file @ 8ad607c6
......@@ -185,8 +185,8 @@ public class IntersceneMatchParameters {
public double min_str_fpn = 0.2; // 0.25; // minimal correlation strength for all but TD-accumulated layer
public double min_str_sum_fpn = 0.5; // 0.8; // minimal correlation strength for TD-accumulated layer
public double min_str = 0.18; // tiles w/o FPN: minimal correlation strength for all but TD-accumulated layer
public double min_str_sum = 0.33; // tiles w/o FPN: minimal correlation strength for TD-accumulated layer
public double min_str = 0.12; //18; // tiles w/o FPN: minimal correlation strength for all but TD-accumulated layer
public double min_str_sum = 0.2; // 0.33; // tiles w/o FPN: minimal correlation strength for TD-accumulated layer
public int min_neibs = 2; // minimal number of strong neighbors (> min_str)
public double weight_zero_neibs = 0.2; // Reduce weight for no-neib (1.0 for all 8)
......@@ -194,7 +194,7 @@ public class IntersceneMatchParameters {
public double half_avg_diff = 0.2; // when L2 of x,y difference from average of neibs - reduce twice
// Detect initial match
public double min_ref_str = 0.22; // For orientations: use only tiles of the reference scene DSI_MAIN is stronger
public double min_ref_str = 0.15; // 0.22; // For orientations: use only tiles of the reference scene DSI_MAIN is stronger
public int pix_step = 4; // Azimuth/tilt search step in pixels
public int search_rad = 10; // Search radius in steps
public double maybe_sum = 1.0; // minimal sum of strengths (will search for the best)
......
src/main/java/com/elphel/imagej/tileprocessor/OpticalFlow.java
View file @ 8ad607c6
......@@ -4382,7 +4382,7 @@ public class OpticalFlow {
debugLevel-2);
} // split cycles to remove output clutter
int debug_scene = -15;
boolean debug2 = false; // true;
boolean debug2 = !batch_mode; // false; // true;
boolean [] reliable_ref = null;
if (min_ref_str > 0.0) {
reliable_ref = quadCLTs[ref_index].getReliableTiles( // will be null if does not exist.
......@@ -4431,9 +4431,26 @@ public class OpticalFlow {
}
scenes_xyzatr[scene_index] = new double [][] {new double[3], use_atr};
} else { // assume linear motion
int num_avg = 1; // 3;
double scale_xyz = 0.0; // 0.5;
int na = num_avg;
if ((scene_index + 1 + na) > ref_index) {
na = ref_index - (scene_index + 1);
}
double [][] last_diff = ErsCorrection.combineXYZATR(
scenes_xyzatr[scene_index+1],
ErsCorrection.invertXYZATR(scenes_xyzatr[scene_index+2]));
scenes_xyzatr[scene_index + 1],
ErsCorrection.invertXYZATR(scenes_xyzatr[scene_index+1 + na]));
for (int i = 0; i < 3; i++) {
last_diff[0][i] /= na;
last_diff[1][i] /= na;
}
for (int i = 0; i < 3; i++) {
last_diff[0][i] *= scale_xyz;
}
// last_diff[0][0] = 0.0;
// last_diff[0][1] = 0.0;
// last_diff[0][2] = 0.0;
scenes_xyzatr[scene_index] = ErsCorrection.combineXYZATR(
scenes_xyzatr[scene_index+1],
last_diff);
......@@ -4606,7 +4623,7 @@ public class OpticalFlow {
quadCLTs[ref_index], // QuadCLT scene,
debugLevel); // int debugLevel);// > 0
for (int nrecalib = 0; nrecalib < photo_num_full; nrecalib++) {
QuadCLT.calibratePhotometric(
QuadCLT.calibratePhotometric2(
clt_parameters, // CLTParameters clt_parameters,
quadCLTs[ref_index], // final QuadCLT ref_scene, // now - may be null - for testing if scene is rotated ref
photo_min_strength, // final double min_strength,
......@@ -4620,7 +4637,8 @@ public class OpticalFlow {
null, // String path, // full name with extension or w/o path to use x3d directory
debugLevel+1);
quadCLT_main.setLwirOffsets(quadCLTs[ref_index].getLwirOffsets());
quadCLT_main.setLwirScales(quadCLTs[ref_index].getLwirScales());
quadCLT_main.setLwirScales (quadCLTs[ref_index].getLwirScales ());
quadCLT_main.setLwirScales2(quadCLTs[ref_index].getLwirScales2());
// Re-read reference and other scenes using new offsets
quadCLTs[ref_index].saveQuadClt(); // to re-load new set of Bayer images to the GPU (do nothing for CPU) and Geometry
quadCLTs[ref_index] = (QuadCLT) quadCLT_main.spawnQuadCLT( // restores dsi from "DSI-MAIN"
......@@ -12478,6 +12496,242 @@ public double[][] correlateIntersceneDebug( // only uses GPU and quad
return coord_motion;
}
/**
* Equalize weights of the motion vectors to boost that of important buy weak one.
* Process overlapping (by half, using shifted cosine weight function) supertiles
* independetly and if it qualifies, increase its tiles weights equlaizing (with
* certain limitations) total supertile weights.
* @param coord_motion [2][tilesX*tilesY][3] input/output arrays.[0][tile][] is
* pXpYD triplet (
* @param stride_hor half of a supertile width
* @param stride_vert half of a supertile height
* @param min_stile_weight minimal total weight of the tiles in a supertile (lower
* will not be modified)
* @param min_stile_number minimal number of defined tiles in a supertile
* @param min_stile_fraction minimal total tile strength compared to the average one
* @param min_disparity minimal disparity of tiles to consider (after filtering)
* @param max_disparity maximal disparity of tiles to consider (after filtering)
* @param weight_add add to each tile after scaling (if total weight < average)
* @param weight_scale scale each tile (if total weight < average)
* If total new weight of a supertile exceeds average - scale each tile to match. If
* lower - keep as is. Only after this step remove tiles (replace with original weight)
* that are discarded by the disparity filter. Multiply result by the the window and
* accumulate (in 4 passes to prevent contentions for the same destination array
*/
public void equalizeMotionVectorsWeights(
final double [][][] coord_motion,
final int tilesX,
final int stride_hor,
final int stride_vert,
final double min_stile_weight,
final int min_stile_number,
final double min_stile_fraction,
final double min_disparity,
final double max_disparity,
final double weight_add,
final double weight_scale)
{
final int tiles = coord_motion[0].length;
final int tilesY = tiles/tilesX;
final int stile_width = 2 * stride_hor;
final int stile_height = 2 * stride_vert;
double [] whor = new double [stride_hor];
double [] wvert = new double [stride_vert];
for (int i = 0; i < stride_hor; i++) whor[i] = 0.5 *(1.0 - Math.cos(Math.PI*(i+0.5)/stride_hor));
for (int i = 0; i < stride_vert; i++) wvert[i] = 0.5 *(1.0 - Math.cos(Math.PI*(i+0.5)/stride_vert));
final int stilesX = (tilesX - 1)/stride_hor; // 9
final int stilesY = (tilesY - 1)/stride_vert; // 7
final int stiles = stilesX * stilesY;
int indx = 0;
final double[] wind = new double[stile_height*stile_width];
for (int iy = 0; iy < stile_height;iy++) {
int iy1 = (iy >= stride_vert) ? (stile_height - 1 - iy) : iy;
for (int ix = 0; ix < stile_width; ix++) {
int ix1 = (ix >= stride_hor) ? (stile_width - 1 - ix) : ix;
wind[indx++] = wvert[iy1] * whor[ix1];
}
}
final double [] stile_weight = new double [stiles];
final int [] stile_number = new int [stiles];
final Thread[] threads = ImageDtt.newThreadArray(threadsMax);
final AtomicInteger ai = new AtomicInteger(0);
final int dbg_stile = -1;
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
public void run() {
for (int sTile = ai.getAndIncrement(); sTile < stiles; sTile = ai.getAndIncrement()) {
if (sTile == dbg_stile) {
System.out.println("normalizeMotionVectorsWeights (): dbg_stile = "+dbg_stile);
}
int sTileX = sTile % stilesX;
int sTileY = sTile / stilesX;
stile_weight[sTile] = 0.0;
int num_tiles = 0; // for partial stiles
for (int iy = 0; iy < stile_height;iy++) {
int tileY = sTileY * stride_vert + iy;
if (tileY >= tilesY) continue;
for (int ix = 0; ix < stile_width; ix++) {
int tileX = sTileX * stride_hor + ix;
if (tileX >= tilesX) continue;
num_tiles++; // for partial stiles
int tile = tileX + tilesX*tileY;
if ((coord_motion[1][tile] != null) && !Double.isNaN(coord_motion[0][tile][2])) {
stile_weight[sTile] += coord_motion[1][tile][2];
stile_number[sTile]++;
}
}
}
stile_weight[sTile] *= 1.0 * stile_height * stile_height / num_tiles; // increase for partiaL stiles
stile_number[sTile] *= stile_height*stile_height;
stile_number[sTile] /= num_tiles;
}
}
};
}
ImageDtt.startAndJoin(threads);
/*
double avg_tile_str = 0.0;
int num_defined = 0;
for (int tile = 0; tile < coord_motion[0].length; tile++) {
if ((coord_motion[1][tile] != null) && !Double.isNaN(coord_motion[0][tile][2])) {
num_defined++;
avg_tile_str +=coord_motion[1][tile][2];
}
}
*/
double sum_stile_str = 0.0;
int num_stiles_defined = 0;
for (int sTile = 0; sTile < stiles; sTile++) {
if (stile_weight[sTile] > 0) {
num_stiles_defined++;
sum_stile_str+=stile_weight[sTile];
}
}
if (num_stiles_defined <=0) {
System.out.println("normalizeMotionVectorsWeights(): no defined supertiles, bailing out");
return;
}
final boolean [] dbg_mod = new boolean [stiles];
final double [] tile_new_strength = new double [tiles]; // accumulate new strengths here
final double avg_stile_str = sum_stile_str / num_stiles_defined;
final double min_combo_weight = Math.max(min_stile_weight, min_stile_fraction * avg_stile_str);
for (int offsy = 0; offsy < 2; offsy++) { // avoiding overlap
final int foffsy = offsy;
final int sty2 = (stilesY + 1 - offsy) / 2;
for (int offsx = 0; offsx < 2; offsx++) {
final int foffsx = offsx;
final int stx2 = (stilesX + 1 - offsx) / 2;
final int st2 = sty2*stx2;
ai.set(0);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
public void run() {
double [] mod_weights = new double [stile_height*stile_width];
for (int indx = ai.getAndIncrement(); indx < st2; indx = ai.getAndIncrement()) {
int stileY = (indx/stx2)*2+foffsy;
int stileX = (indx%stx2)*2+foffsx;
int sTile = stileX + (stilesX * stileY);
if (sTile == dbg_stile) {
System.out.println("normalizeMotionVectorsWeights (): dbg_stile = "+dbg_stile);
}
boolean keep_old = false;
// check this tile qualifies:
//stile_number
if (stile_number[sTile] < min_stile_number) {
keep_old = true;
}
if (stile_weight[sTile] < min_combo_weight) {
keep_old = true;
}
if (stile_weight[sTile] >= avg_stile_str) { // already strong enough
keep_old = true;
}
Arrays.fill(mod_weights,0);
double sum_weights = 0.0;
int num_tiles = 0; // for partial stiles
for (int iy = 0; iy < stile_height;iy++) {
int tileY = stileY * stride_vert + iy;
if (tileY >= tilesY) continue;
for (int ix = 0; ix < stile_width; ix++) {
int tileX = stileX * stride_hor + ix;
if (tileX >= tilesX) continue;
int tile = tileX + tilesX*tileY;
num_tiles ++;
if ((coord_motion[1][tile] != null) && !Double.isNaN(coord_motion[0][tile][2])) {
int ltile = ix + iy * stile_width;
mod_weights[ltile] = keep_old ?
coord_motion[1][tile][2] :
(weight_add + coord_motion[1][tile][2] ) * weight_scale;
sum_weights += mod_weights[ltile];
}
}
}
sum_weights *= 1.0 * stile_height * stile_height / num_tiles ; // increase for partial tiles
if (!keep_old) {
if (sum_weights > avg_stile_str) { // scale back
double s = avg_stile_str/sum_weights;
for (int ltile = 0; ltile < mod_weights.length; ltile++) {
mod_weights[ltile] *= s;
}
}
for (int iy = 0; iy < stile_height;iy++) {
int tileY = stileY * stride_vert + iy;
if (tileY >= tilesY) continue;
for (int ix = 0; ix < stile_width; ix++) {
int tileX = stileX * stride_hor + ix;
if (tileX >= tilesX) continue;
int tile = tileX + tilesX*tileY;
int ltile = ix + iy * stile_width;
// remove out of range disparity
if (coord_motion[0][tile] != null) {
double disp = coord_motion[0][tile][2]; // shopuld be non-null
if ((disp < min_disparity) || (disp > max_disparity)) { // min/max = NaN - OK
mod_weights[ltile] = coord_motion[1][tile][2]; // use original value
}
}
}
}
dbg_mod[sTile] = true;
}
// multiply by window and accumulate
for (int iy = 0; iy < stile_height;iy++) {
int tileY = stileY * stride_vert + iy;
if (tileY >= tilesY) continue;
for (int ix = 0; ix < stile_width; ix++) {
int tileX = stileX * stride_hor + ix;
if (tileX >= tilesX) continue;
int tile = tileX + tilesX*tileY;
int ltile = ix + iy * stile_width;
// wind
tile_new_strength[tile] += wind[ltile] * mod_weights[ltile];
}
}
}
}
};
}
ImageDtt.startAndJoin(threads);
}
}
ai.set(0);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
public void run() {
for (int nTile = ai.getAndIncrement(); nTile < tiles; nTile = ai.getAndIncrement()) {
if (tile_new_strength[nTile] > 0.0) { // assuming ((coord_motion[1][nTile] != null) && !Double.isNaN(coord_motion[0][nTile][2]))
if (coord_motion[1][nTile] == null) {
System.out.println("coord_motion[1]["+nTile+"] == null, tileX="+(nTile%tilesX)+", tileY="+(nTile/tilesX));
} else {
coord_motion[1][nTile][2] = tile_new_strength[nTile]; // replace modified
}
}
}
}
};
}
ImageDtt.startAndJoin(threads);
return;
}
public static boolean [] getMovementMask(
CLTParameters clt_parameters,
......@@ -13123,6 +13377,7 @@ public double[][] correlateIntersceneDebug( // only uses GPU and quad
double[] camera_atr0 = camera_atr.clone();
double [][][] coord_motion = null;
boolean show_corr_fpn = debug_level > -1; // -3; *********** Change to debug FPN correleation ***
boolean run_equalize = false;
int nlma = 00;
for (; nlma < clt_parameters.imp.max_cycles; nlma ++) {
......@@ -13148,6 +13403,75 @@ public double[][] correlateIntersceneDebug( // only uses GPU and quad
System.out.println("adjustPairsLMAInterscene() returned null");
return null;
}
int eq_stride_hor = 8;
int eq_stride_vert = 8;
double eq_min_stile_weight = 1.0;
int eq_min_stile_number = 10;
double eq_min_stile_fraction = 0.05;
double eq_min_disparity = 5;
double eq_max_disparity = 100;
double eq_weight_add = 0.1;
double eq_weight_scale = 10;
if (run_equalize && near_important) {
TileProcessor tp = reference_QuadClt.getTileProcessor();
int tilesX = tp.getTilesX();
int tilesY = tp.getTilesY();
// backup coord_motion[1][][2] // strength
double [] strength_backup = new double [coord_motion[1].length];
for (int i = 0; i < strength_backup.length; i++) if (coord_motion[1][i] != null) {
strength_backup[i] = coord_motion[1][i][2];
}
while (run_equalize) {
// restore
for (int i = 0; i < strength_backup.length; i++) if (coord_motion[1][i] != null) {
coord_motion[1][i][2] = strength_backup[i];
}
equalizeMotionVectorsWeights(
coord_motion, // final double [][][] coord_motion,
tilesX, // final int tilesX,
eq_stride_hor, // final int stride_hor,
eq_stride_vert, // final int stride_vert,
eq_min_stile_weight, // final double min_stile_weight,
eq_min_stile_number, // final int min_stile_number,
eq_min_stile_fraction, // final double min_stile_fraction,
eq_min_disparity, // final double min_disparity,
eq_max_disparity, // final double max_disparity,
eq_weight_add, // final double weight_add,
eq_weight_scale); // final double weight_scale)
String [] mvTitles = {"dx", "dy","conf", "conf0", "pX", "pY","Disp","defined"}; // ,"blurX","blurY", "blur"};
double [][] dbg_img = new double [mvTitles.length][tilesX*tilesY];
for (int l = 0; l < dbg_img.length; l++) {
Arrays.fill(dbg_img[l], Double.NaN);
}
for (int nTile = 0; nTile < coord_motion[0].length; nTile++) {
if (coord_motion[0][nTile] != null) {
for (int i = 0; i <3; i++) {
dbg_img[4+i][nTile] = coord_motion[0][nTile][i];
}
}
dbg_img[3] = strength_backup;
if (coord_motion[1][nTile] != null) {
for (int i = 0; i <3; i++) {
dbg_img[0+i][nTile] = coord_motion[1][nTile][i];
}
}
dbg_img[7][nTile] = ((coord_motion[0][nTile] != null)?1:0)+((coord_motion[0][nTile] != null)?2:0);
}
(new ShowDoubleFloatArrays()).showArrays( // out of boundary 15
dbg_img,
tilesX,
tilesY,
true,
scene_QuadClt.getImageName()+"-"+reference_QuadClt.getImageName()+"-coord_motion-eq",
mvTitles);
}
}
intersceneLma.prepareLMA(
camera_xyz0, // final double [] scene_xyz0, // camera center in world coordinates (or null to use instance)
camera_atr0, // final double [] scene_atr0, // camera orientation relative to world frame (or null to use instance)
......@@ -13255,6 +13579,12 @@ public double[][] correlateIntersceneDebug( // only uses GPU and quad
true,
scene_QuadClt.getImageName()+"-"+reference_QuadClt.getImageName()+"-CORR-FPN",
fpn_dbg_titles);
}
......
src/main/java/com/elphel/imagej/tileprocessor/QuadCLT.java
View file @ 8ad607c6
......@@ -45,6 +45,7 @@ import com.elphel.imagej.cameras.CLTParameters;
import com.elphel.imagej.cameras.ColorProcParameters;
import com.elphel.imagej.cameras.EyesisCorrectionParameters;
import com.elphel.imagej.common.DoubleGaussianBlur;
import com.elphel.imagej.common.PolynomialApproximation;
import com.elphel.imagej.common.ShowDoubleFloatArrays;
import com.elphel.imagej.correction.CorrectionColorProc;
import com.elphel.imagej.correction.EyesisCorrections;
......@@ -2426,20 +2427,234 @@ public class QuadCLT extends QuadCLTCPU {
}
double [] offsets_old = ref_scene.getLwirOffsets();
double [] scales_old = ref_scene.getLwirScales();
double [] scales2_old = ref_scene.getLwirScales2();
double [] offsets_new = new double[num_sens];
double [] scales_new = new double[num_sens];
double [] scales2_new = new double[num_sens];
for (int n = 0; n < num_sens; n++) {
scales_new[n] = scales_old[n]/scales[n];
// offsets_new[n] = offsets_old[n] - offsets[n] / scales_old[n];
offsets_new[n] = offsets_old[n] + offsets[n] / scales_old[n];
}
System.out.println("calibratePhotometric() Updated calibration:");
for (int n = 0; n < num_sens; n++) {
System.out.println(String.format("%2d: %8.4f %8.6f", n,offsets_new[n],scales_new[n]));
System.out.println(String.format("%2d: %8.4f %8.6f %8.6f", n,offsets_new[n],scales_new[n], scales2_new[n]));
}
System.out.println();
ref_scene.setLwirOffsets(offsets_new);
ref_scene.setLwirOffsets (offsets_new);
ref_scene.setLwirScales (scales_new);
ref_scene.setLwirScales2 (scales2_new);
return true;
}
public static boolean calibratePhotometric2( // quadratic
CLTParameters clt_parameters,
final QuadCLT ref_scene, // now - may be null - for testing if scene is rotated ref
final double min_strength,
final double max_diff, // 30.0
final int num_refines, // 2
final double [][] combo_dsn_final, // double [][] combo_dsn_final, // dls,
int threadsMax,
final boolean debug)
{
// filter disparity by LMA only, same bg and fg
double [] disparity_ref= combo_dsn_final[OpticalFlow.COMBO_DSN_INDX_DISP].clone();
for (int i = 00; i < disparity_ref.length; i++) {
if (combo_dsn_final[OpticalFlow.COMBO_DSN_INDX_STRENGTH][i] < min_strength) {
disparity_ref[i] = Double.NaN;
} else if (combo_dsn_final[OpticalFlow.COMBO_DSN_INDX_DISP_BG_ALL][i] !=
combo_dsn_final[OpticalFlow.COMBO_DSN_INDX_DISP][i]) {
disparity_ref[i] = Double.NaN;
}
}
ImagePlus img_ref = renderGPUFromDSI(
-1, // final int sensor_mask,
false, // final boolean merge_channels,
null, // final Rectangle full_woi_in, // show larger than sensor WOI in tiles (or null)
clt_parameters, // CLTParameters clt_parameters,
disparity_ref, // double [] disparity_ref,
OpticalFlow.ZERO3, // final double [] scene_xyz, // camera center in world coordinates
OpticalFlow.ZERO3, // final double [] scene_atr, // camera orientation relative to world frame
ref_scene, // final QuadCLT scene,
ref_scene, // final QuadCLT ref_scene, // now - may be null - for testing if scene is rotated ref
false, // final boolean toRGB,
true, // final boolean show_nan,
"PHOTOMETRIC", // String suffix,
threadsMax, // int threadsMax,
-2); // final int debugLevel);
img_ref.show();
ImageStack imageStack = img_ref.getStack();
int num_sens=imageStack.getSize();
float [] fpixels;
double [][] dpixels = new double [num_sens][];
for (int n = 0; n < num_sens; n++) {
fpixels = (float[]) imageStack.getPixels(n + 1);
dpixels[n] = new double [fpixels.length];
for (int i = 0; i < fpixels.length; i++) {
dpixels[n][i] = fpixels[i];
}
}
boolean quadratic = true;
// double [][] dpix_orig = new double[num_sens][];
// for (int n = 0; n < num_sens; n++) {
// dpix_orig[n] = dpixels[n].clone();
// }
int width = img_ref.getWidth();
int height = img_ref.getHeight();
int len = width* height;
double [] avg_pix = new double [len];
double [] offsets = new double[dpixels.length];
double [] scales = new double[dpixels.length];
double s0 = 0.0;
double sx= 0.0;
double sx2 = 0.0;
double [] sy = new double[num_sens];
double [] sxy = new double[num_sens];
boolean [] good_pix = new boolean[len];
double [][] pa_coeff = new double[num_sens][];
Arrays.fill(good_pix, true);
for (int nref = 0; nref < num_refines; nref++) {
Arrays.fill(avg_pix, 0.0);
int num_good = 0;
for (int i = 0; i < len; i++) {
for (int n = 0; n < num_sens; n++) {
avg_pix[i]+=dpixels[n][i];
good_pix[i] &= !Double.isNaN(dpixels[n][i]);
}
avg_pix[i] /= dpixels.length;
if (good_pix[i]) {
num_good++;
}
}
double [][] pa_data = new double [num_good][2];
for (int nsens = 0; nsens < num_sens; nsens++) {
int indx = 0;
for (int i = 0; i < len; i++) if (good_pix[i]){
pa_data[indx][0] = dpixels[nsens][i];
pa_data[indx][1] = avg_pix[i];
indx++;
}
// quadratic
pa_coeff[nsens] =(new PolynomialApproximation(0)).polynomialApproximation1d(pa_data, quadratic ? 2 : 1);
}
if (debug) {
System.out.println("calibratePhotometric() nref="+nref);
for (int n = 0; n < num_sens; n++) {
System.out.println(String.format("%2d: %8.4f %8.6f %8.6f", n,pa_coeff[n][0],pa_coeff[n][1], 1e6*pa_coeff[n][2]));
}
System.out.println();
double [][] diffs = new double [num_sens][len];
for (int n = 0; n < num_sens; n++) {
Arrays.fill(diffs[n], Double.NaN);
}
for (int i = 0; i < len; i++) if (good_pix[i]) { // if (!Double.isNaN(avg_pix[i])){
for (int n = 0; n < num_sens; n++) {
// diffs[n][i] = dpixels[n][i] - (scales[n] * avg_pix[i] + offsets[n]);
diffs[n][i] = -(avg_pix[i] - pa_coeff[n][2] * dpixels[n][i] * dpixels[n][i] - pa_coeff[n][1] * dpixels[n][i] - pa_coeff[n][0]);
}
}
(new ShowDoubleFloatArrays()).showArrays( // out of boundary 15
diffs,
width,
height,
true,
"photometric-quad-err"+nref);
}
Arrays.fill(offsets,0.0);
Arrays.fill(scales,0.0);
s0 = 0.0;
sx= 0.0;
sx2 = 0.0;
Arrays.fill(sy,0.0);
Arrays.fill(sxy,0.0);
for (int i = 0; i < len; i++) if (good_pix[i]) { // !Double.isNaN(avg_pix[i])){
s0 += 1.0;
sx += avg_pix[i];
sx2 += avg_pix[i] * avg_pix[i];
for (int n = 0; n < num_sens; n++) {
sy[n] += dpixels[n][i];
sxy[n] += dpixels[n][i] * avg_pix[i];
}
}
for (int n = 0; n < num_sens; n++) {
double d = s0 * sx2 + sx * sy[n];
scales[n] = (sxy[n] * s0 + sy[n] * sy[n]) / d;
offsets[n] = (sy[n] * sx2 -sxy[n]*sx) / d;
}
if (debug) {
System.out.println("calibratePhotometric() nref="+nref);
for (int n = 0; n < num_sens; n++) {
System.out.println(String.format("%2d: %8.4f %8.6f", n,offsets[n],scales[n]));
}
System.out.println();
double [][] diffs = new double [num_sens][len];
for (int n = 0; n < num_sens; n++) {
Arrays.fill(diffs[n], Double.NaN);
}
for (int i = 0; i < len; i++) if (good_pix[i]) { // if (!Double.isNaN(avg_pix[i])){
for (int n = 0; n < num_sens; n++) {
diffs[n][i] = dpixels[n][i] - (scales[n] * avg_pix[i] + offsets[n]);
}
}
(new ShowDoubleFloatArrays()).showArrays( // out of boundary 15
diffs,
width,
height,
true,
"photometric-err"+nref);
// dpix_orig[n] = dpixels[n].clone();
double [][] corrected = new double [num_sens][len];
for (int n = 0; n < num_sens; n++) {
Arrays.fill(corrected[n], Double.NaN);
for (int i = 0; i < len; i++) if (!Double.isNaN(dpixels[n][i])){
corrected[n][i] = (dpixels[n][i] - offsets[n])/scales[n];
}
}
(new ShowDoubleFloatArrays()).showArrays( // out of boundary 15
corrected,
width,
height,
true,
"photometric-corr"+nref);
}
//max_diff
if (nref < (num_refines-1)) {
for (int i = 0; i < len; i++) if (good_pix[i]) { // !Double.isNaN(avg_pix[i])){
for (int n = 0; n < num_sens; n++) {
double diff = Math.abs(dpixels[n][i] - (scales[n] * avg_pix[i] + offsets[n]));
if (diff > max_diff) {
// dpixels[n][i] = Double.NaN;
good_pix[i] = false;
break;
}
}
}
}
}
double [] offsets_old = ref_scene.getLwirOffsets();
double [] scales_old = ref_scene.getLwirScales();
double [] scales2_old = ref_scene.getLwirScales2();
double [] offsets_new = new double[num_sens];
double [] scales_new = new double[num_sens];
double [] scales2_new = new double[num_sens];
for (int n = 0; n < num_sens; n++) {
scales_new[n] = scales_old[n]/scales[n];
offsets_new[n] = offsets_old[n] + offsets[n] / scales_old[n];
}
System.out.println("calibratePhotometric() Updated calibration:");
for (int n = 0; n < num_sens; n++) {
System.out.println(String.format("%2d: %8.4f %8.6f %8.6f", n,offsets_new[n],scales_new[n], scales2_new[n]));
}
System.out.println();
ref_scene.setLwirOffsets (offsets_new);
ref_scene.setLwirScales (scales_new);
ref_scene.setLwirScales2 (scales2_new);
return true;
}
......
src/main/java/com/elphel/imagej/tileprocessor/QuadCLTCPU.java
View file @ 8ad607c6
......@@ -153,7 +153,7 @@ public class QuadCLTCPU {
boolean is_aux = false;
double [] lwir_offsets = null; // per image subtracted values
double [] lwir_scales = null; // per image scales
//double [] lwir_scales2 = null; // per image quadratic scales
double [] lwir_scales2 = null; // per image quadratic scales
@Deprecated
double lwir_offset = Double.NaN; // average of lwir_offsets[]
// hot and cold are calculated during autoranging (when generating 4 images for restored (added lwir_offset)
......@@ -266,6 +266,7 @@ public class QuadCLTCPU {
// this.is_mono = qParent.is_mono;
this.lwir_offsets = ErsCorrection.clone1d(qParent.lwir_offsets);
this.lwir_scales = ErsCorrection.clone1d(qParent.lwir_scales);
this.lwir_scales2 = ErsCorrection.clone1d(qParent.lwir_scales2);
this.lwir_offset = qParent.lwir_offset;
this.lwir_cold_hot = ErsCorrection.clone1d(qParent.lwir_cold_hot);
this.ds_from_main = ErsCorrection.clone2d(qParent.ds_from_main);
......@@ -1798,6 +1799,12 @@ public class QuadCLTCPU {
}
return lwir_scales;
}
public double [] getLwirScales2() {
if (lwir_scales2 == null) {
lwir_scales2 = new double [getNumSensors()]; // all 0;
}
return lwir_scales2;
}
public void setLwirOffsets(double [] offsets) {
lwir_offsets = offsets; // will need to update properties!
if (offsets != null) {
......@@ -1812,6 +1819,9 @@ public class QuadCLTCPU {
public void setLwirScales(double [] scales) {
lwir_scales = scales; // will need to update properties!
}
public void setLwirScales2(double [] scales2) {
lwir_scales2 = scales2; // will need to update properties!
}
public double [] getColdHot() { // USED in lwir
return lwir_cold_hot;
......@@ -2011,6 +2021,10 @@ public class QuadCLTCPU {
properties.setProperty(prefix+"lwir_scales",
IntersceneMatchParameters.doublesToString(this.lwir_scales));
}
if (this.lwir_scales2 != null) {
properties.setProperty(prefix+"lwir_scales2",
IntersceneMatchParameters.doublesToString(this.lwir_scales2));
}
}
......@@ -2053,6 +2067,12 @@ public class QuadCLTCPU {
properties.setProperty(this_prefix+"lwir_scales",
IntersceneMatchParameters.doublesToString(this.lwir_scales));
}
if (other_properties.getProperty(other_prefix+"lwir_scales2")!=null) {
this.lwir_scales2= IntersceneMatchParameters.StringToDoubles(
other_properties.getProperty(other_prefix+"lwir_scales2"),0);
properties.setProperty(this_prefix+"lwir_scales2",
IntersceneMatchParameters.doublesToString(this.lwir_scales2));
}
/*
......@@ -2173,6 +2193,10 @@ public class QuadCLTCPU {
this.lwir_scales= IntersceneMatchParameters.StringToDoubles(
properties.getProperty(prefix+"lwir_scales"),0);
}
if (properties.getProperty(prefix+"lwir_scales2")!=null) {
this.lwir_scales2= IntersceneMatchParameters.StringToDoubles(
properties.getProperty(prefix+"lwir_scales2"),0);
}
......@@ -5572,11 +5596,13 @@ public class QuadCLTCPU {
}
double [] offsets = getLwirOffsets();
double [] scales = getLwirScales();
double [] scales2 = getLwirScales2();
channelLwirApplyEqualize( // now apply (was part of channelLwirEqualize() )
channelFiles, // int [] channelFiles,
imp_srcs, // ImagePlus [] imp_srcs,
offsets, // double [] offsets,
scales, // double [] scales,
scales2, // double [] scales2,
threadsMax,
debugLevel);
}
......@@ -6162,6 +6188,7 @@ public class QuadCLTCPU {
ImagePlus [] imp_srcs,
double [] offsets,
double [] scales,
double [] scales2,
final int threadsMax,
int debugLevel){
final Thread[] threads = ImageDtt.newThreadArray(threadsMax);
......@@ -6174,9 +6201,11 @@ public class QuadCLTCPU {
if (nFile >=0) {
float fd = (float)offsets[srcChannel];
float fscale = (float) scales[srcChannel];
float fscale2 = (float) scales2[srcChannel];
float [] pixels = (float []) imp_srcs[srcChannel].getProcessor().getPixels();
for (int i = 0; i < pixels.length; i++) {
pixels[i] = (pixels[i] - fd) * fscale;
float poffs = (pixels[i] - fd);
pixels[i] = poffs * fscale + poffs*poffs*fscale2;
}
}
}
......
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