/usr/include/rtd/ImageTemplates.icc is in skycat 3.1.2+starlink1~b+dfsg-5.
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* E.S.O. - VLT project
*
* "@(#) $Id: ImageTemplates.icc,v 1.1.1.1 2009/03/31 14:11:52 cguirao Exp $"
*
* ImageTemplates.C - template member functions for classes derived from
* class ImageData (not C++ templates, uses cpp macros)
*
* See the man page ImageData(3) for a complete description of this class
* hierarchy.
*
* who when what
* -------------- -------- ----------------------------------------
* Allan Brighton 05/10/95 Created
* Peter W. Draper 29/01/97 Added FITS_LONG changes (for alpha 64 longs)
* P.Biereichel 30/06/97 Changed parameters in getValues() for pixel table
* Peter W. Draper 23/02/98 Changed min/max calculations to use more
* pixels (too many occurences of "strange" limits).
* 06/03/98 Added changes to support XImage depths
* greater than one byte.
* pbiereic 22/03/99 Added on-the-fly subtraction.
* Peter W. Draper 17/08/00 Changed getMinMax slightly. This now
* checks if the total height of the image
* is shown, rather than just testing
* y0_. This could be wrong for zoomed
* pbiereic 21/06/00 Fixed "array out of bounds" in getMinMax()
* Peter W. Draper 19/03/01 Made sure that x1 and y1 in getMinMax,
* never run off the edges of image.
* pbiereic 17/02/03 Native byte order routines revised
* Peter W. Draper 30/05/03 Skip runs of blank pixels in median estimate
* pbiereic 18/06/04 Added experimental sampling methods
* Peter W. Draper 01/11/06 Changed getMinMax to deal with images that
* have a dimension of 1 (but not both).
* 08/01/07 Changed getMinMax to deal with 1x1 case too.
* 16/07/07 When first pixel is blank or NaN make sure
* failed check for a valid pixel tests both
* blank and NaN, not just NaN.
* 16/04/08 Added growAndShrink() to allow scales
* to have positive and negative values
* at the same time.
* 19/06/09 Change initBlankValue to use the cached
* blankValue_ and make public (allows change).
* pbiereic 12/08/07 added support for data types double and long long int
* Peter W. Draper 17/05/12 Merged skycat double version created by pbiereic.
*
* This file is included in the .C files for classes derived from class
* ImageData. The file defines a number of member functions that are
* always the same, except for the underlying raw image data type. The
* member functions are implemented in the derived classes for speed
* (otherwise we would have to call virtual functions on each pixel...)
*
* Before including, the following #defines need to be made:
*
* #define CLASS_NAME <...> - as the name of the derived class
* #define DATA_TYPE as the raw image data type (short, long, float,...)
* #define NTOH(x) to be just (x) if you're sure your type never requires
* byte-swapping. Otherwise leave it undefined and the
* code below should do the right thing.
* #define ISNAN(x) Only for floating point types, returns true if x is a NAN
*/
/*
* For all member functions within this file use the inline function getVal()
* instead of referencing the raw image directly. getVal() returns the raw
* image pixel value or the subtracted value if a bias frame was selected.
* Before using getVal() initialize this function with initGetVal().
*/
#include <iostream>
#include <cassert>
#include "define.h"
// This is a no-op for non-floating point data types. This macro is
// defined as isnan(x) for floating point types.
#ifndef ISNAN
#define ISNAN(x) 0
#endif
/*
* getVal() is an inline function which subtracts on-the-fly a
* bias pixel if a bias frame is selected.
* p - is a pointer to the raw image
* idx - is an index to the image
*
* looks "big" but it isn't (gcc assembler code was checked).
*/
inline DATA_TYPE CLASS_NAME::getVal(DATA_TYPE* p, int idx)
{
// return pixel value if bias subtraction is off
if (! ImageData::biasInfo_->on)
return (DATA_TYPE)NTOH(*(p + idx));
if ( ! bias_swap_bytes_) {
// return faster if image dimensions and types are the same
if (ImageData::biasInfo_->sameTypeAndDims)
return ((DATA_TYPE)NTOH(*(p + idx)) -
(DATA_TYPE)((DATA_TYPE)(*((DATA_TYPE*)ImageData::biasInfo_->ptr + idx))));
register biasINFO* bias = ImageData::biasInfo_;
register int x = idx % width_ + startX_;
register int y = idx / width_ + startY_;
// if pixel is not within the boundary of the bias image return pixel value
if (x < 0 || x >= bias->width || y < 0 || y >= bias->height)
return NTOH(*(p + idx));
register int biasIdx = y * bias->width + x;
switch (bias->type) {
case BYTE_IMAGE:
case X_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((byte)(*((byte *)bias->ptr + biasIdx)));
case USHORT_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((ushort)(*((ushort *)bias->ptr + biasIdx)));
case SHORT_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((short)(*((short *)bias->ptr + biasIdx)));
case LONG_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((int)(*((int *)bias->ptr + biasIdx)));
case FLOAT_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((float)(*((float *)bias->ptr + biasIdx)));
case DOUBLE_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((double)(*((double *)bias->ptr + biasIdx)));
case LONGLONG_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((long long)(*((long long *)bias->ptr + biasIdx)));
default:
return (DATA_TYPE)NTOH(*(p + idx));
}
}
else {
register biasINFO* bias = ImageData::biasInfo_;
register int x = idx % width_ + startX_;
register int y = idx / width_ + startY_;
// if pixel is not within the boundary of the bias image return pixel value
if (x < 0 || x >= bias->width || y < 0 || y >= bias->height)
return NTOH(*(p + idx));
register int biasIdx = y * bias->width + x;
switch (bias->type) {
case BYTE_IMAGE:
case X_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((byte)(*((byte *)bias->ptr + biasIdx)));
case USHORT_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((ushort)SWAP16(*((ushort *)bias->ptr + biasIdx)));
case SHORT_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((short)SWAP16(*((short *)bias->ptr + biasIdx)));
case LONG_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((int)SWAP32(*((int *)bias->ptr + biasIdx)));
case FLOAT_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((float)SWAP_FLOAT(*((float *)bias->ptr + biasIdx)));
case DOUBLE_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((double)SWAP_DOUBLE(*((double *)bias->ptr + biasIdx)));
case LONGLONG_IMAGE:
return (DATA_TYPE)NTOH(*(p + idx)) - (DATA_TYPE)((long long)SWAP64(*((long long *)bias->ptr + biasIdx)));
default:
return (DATA_TYPE)NTOH(*(p + idx));
}
}
}
/*
* Scan the image to find the min and max values and set the member
* variables accordingly. To save time, only the visible area of the
* image is examined (x0_, y0_, x1_ and y1_ are set each time the
* image is updated, however they are initially set to the entire
* image).
* The result is that the member variables minValue_ and maxValue_
* are set.
*/
void CLASS_NAME::getMinMax()
{
DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
int p;
register DATA_TYPE value;
initGetVal(); // init flag for speeding up bias subtraction
// use area of image that is visible.
// if we are looking at the whole image, ignore the margin
int w = x1_ - x0_ + 1, h = y1_ - y0_ + 1;
int xmargin = 0, ymargin = 0;
if (w == width_)
xmargin = int(w * 0.02);
if ( h == height_ ) // PWD: change here, test was y0_ == 0
ymargin = int(h * 0.02);
int x0 = x0_ + xmargin;
int y0 = y0_ + ymargin;
int x1 = min( x1_ - xmargin, width_ - 1 ); // PWD: stop running
int y1 = min( y1_ - ymargin, height_ - 1 );// off edges
w = x1 - x0 + 1;
h = y1 - y0 + 1;
if ( w < 1 || h < 1 || ( w == 1 && h == 1 )) {
if (area_ > 0) {
minValue_ = maxValue_ = getVal(rawImage, 0);
} else {
minValue_ = maxValue_ = 0;
}
return;
}
// set the x, y increments so that not every pixel or line is
// examined on large images
int xincr = w/256;
if (xincr == 0)
xincr++;
int yincr = h/256;
if (yincr == 0)
yincr++;
if (x1 >= x1_ - xincr) {
x1 = x1_ - xincr;
if ( x1 < 0 ) {
x1 = 1;
}
}
if (y1 >= y1_ - yincr) {
y1 = y1_ - yincr;
if ( y1 < 0 ) {
y1 = 1;
}
}
// try to speed things up a bit on large images:
// don't examine every pixel, just look at a few sample lines
p = y0*width_+x0; // first pixel in region to examine
value = getVal(rawImage, p);
// ignore BLANK pixels. For efficiency, we only check the flag once
int end = area_;
if (haveBlank_) {
// make sure starting min/max values are not the BLANK pixel
while(value == blank_ || ISNAN(value)) {
p += 10; // check another pixel
if (p >= end)
break;
value = getVal(rawImage, p);
}
if (value == blank_ || ISNAN(value))
value = 0;
minValue_ = maxValue_ = value;
for (int y = y0; y <= y1; y+=yincr) {
p = y*width_+x0;
if (p >= end)
break;
for (int x = x0; x <= x1; x+=xincr, p+=xincr) {
if ((value = getVal(rawImage, p)) == blank_ || ISNAN(value))
continue;
if (value < minValue_)
minValue_ = value;
else if (value > maxValue_)
maxValue_ = value;
}
}
}
else {
// note that for non-float types, the ISNAN call is optimized away
while(ISNAN(value)) {
p += 10; // check another pixel
if (p >= end)
break;
value = getVal(rawImage, p);
}
if (ISNAN(value))
value = 0;
minValue_ = maxValue_ = value;
for (int y = y0; y <= y1; y+=yincr) {
p = y*width_+x0;
if (p >= end)
break;
for (int x = x0; x <= x1; x+=xincr, p+=xincr) {
value = getVal(rawImage, p);
if (ISNAN(value))
continue;
if (value < minValue_)
minValue_ = value;
else if (value > maxValue_)
maxValue_ = value;
}
}
}
}
/*
* print the coordinates and raw data value at the given x,y image
* coords to the buffer
*
* A "-" is printed if the x,y coords are out of range.
* "blank" is printed if the pixel is blank.
*/
char* CLASS_NAME::getValue(char* buf, double x, double y)
{
DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
DATA_TYPE value;
initGetVal(); // init flag for bias subtraction
int ix, iy;
if (getIndex(x, y, ix, iy) != 0)
sprintf(buf, "%.1f %.1f -", x, y);
else {
value = getVal(rawImage, iy*width_+ix);
if (haveBlank_ && value == blank_)
sprintf(buf, "%.1f %.1f blank", x, y);
else
sprintf(buf, "%.1f %.1f %g", x, y, scaleValue(value));
}
return buf;
}
/*
* return the value at the x,y image coords as a double.
*
* The input x,y is assumed to be in image coords.
* If the coords are out of range, 0.0 is returned.
*/
double CLASS_NAME::getValue(double x, double y)
{
DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
int ix, iy;
initGetVal(); // init flag for bias subtraction
if (getIndex(x, y, ix, iy) != 0)
return 0.0;
return scaleValue(getVal(rawImage, iy*width_+ix));
}
/*
* print the X, Y coordinates, raw data value and World Coordinates
* at the given x,y image coords to the given buffers.
*
* rx and ry are the image coordinates to use to access the pixel value. This might
* be different than x,y, since x,y are the logical image coordinates, assuming the
* image starts at 1,1, which might not actually be the case.
*
* A blank value is printed if the rx,ry coords are out of range.
*
* note: x, y and rx,ry are expected in image coords, while in the result,
* xStr and yStr are in "chip" coords, since they should be displayed.
*/
void CLASS_NAME::getValues(double x, double y, double rx, double ry,
char* xStr, char* yStr, char* valueStr,
char* raStr, char* decStr, char* equinoxStr)
{
initGetVal(); // init flag for speeding up bias subtraction
// display chip coords for x and y
double cx = x, cy = y;
imageToChipCoords(cx, cy);
sprintf(xStr, "%.1f", cx);
sprintf(yStr, "%.1f", cy);
*raStr = '\0';
*decStr = '\0';
*equinoxStr = '\0';
if (wcs().isWcs()) {
char buf[80];
wcs().pix2wcs(x, y, buf, sizeof(buf), 1);
sscanf(buf, "%s %s %s", raStr, decStr, equinoxStr);
}
// get integer index in raw image for pixel value
int ix, iy;
*valueStr = '\0';
if (getIndex(rx, ry, ix, iy) == 0) {
DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
DATA_TYPE value = getVal(rawImage, iy*width_+ix);
if (haveBlank_ && value == blank_)
strcpy(valueStr, "blank");
else
sprintf(valueStr, "%g", scaleValue(value));
}
}
/*
* Fill the given array with the pixel values surrounding the given point.
* nrows and ncols give the dimensions of the array. Any values that are outside
* of the image or are blank (BLANK keyword) are set to -HUGE_VAL (If "flag"
* is non-zero, values outside the image are not changed).
*
* Note: it is assumed that nrows and ncols are odd numbers and that the array
* is one row and column larger (nrows+1 x ncols+1), so that it can hold the
* X and Y index headings.
*
* rx and ry are the image coordinates to use to access the pixel value. This might
* be different than x,y, since x,y are the logical image coordinates, assuming the
* image starts at 1,1, which might not actually be the case.
*
* note: x, y and rx,ry are expected in image coords, however the coordinates in the
* result are "chip" coords, since they should be displayed.
*
*/
void CLASS_NAME::getValues(double x, double y, double rx, double ry, double* ar,
int nrows, int ncols, int flag)
{
DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
initGetVal(); // init flag for speeding up bias subtraction
int m = ncols/2;
int n = nrows/2;
int w = ncols+1;
int i, j;
// get pixel index
int ix, iy;
// insert the x coord headings
for (i = 0; i < ncols; i++) {
double cx = x+(i-m);
imageToChipCoords(cx);
ar[i+1] = cx; // X coord top heading
}
for (j = 0; j < nrows; j++) {
double cy = y+(j-n);
imageToChipCoords(cy);
ar[(j+1)*w] = cy; // Y coord left heading
for (i = 0; i < ncols; i++) {
if (getIndex(rx+(i-m), ry+(j-n), ix, iy) == 0) {
DATA_TYPE value = getVal(rawImage, iy*width_+ix);
if (haveBlank_ && value == blank_)
ar[(j+1)*w+i+1] = -HUGE_VAL;
else
ar[(j+1)*w+i+1] = scaleValue(value);
}
else if (! flag) {
ar[(j+1)*w+i+1] = -HUGE_VAL;
}
}
}
}
/*
* Fill the given array with the pixel values (converted to floats as needed)
* at the given x,y image pos, width and height.
*
* The array should be large enough for at least (w x h) floats.
*
* Any values that are outside of the image are set to blank or 0, if there
* is no blank pixel value defined (If "flag" is non-zero, values outside
* the image are not changed).
*
* Note: x and y are expected in image coordinates
*/
void CLASS_NAME::getValues(double x, double y, int w, int h, float* ar, int flag)
{
DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
int i, j;
int ix, iy;
DATA_TYPE value;
initGetVal(); // init flag for speeding up bias subtraction
getIndex(x, y, ix, iy);
for (j = 0; j < h; j++) {
for (i = 0; i < w; i++) {
int rx = ix+i, ry = iy+j;
if (rx >= 0 && ry >= 0 && rx < width_ && ry < height_) {
value = getVal(rawImage, ry*width_+rx);
if (haveBlank_ && value == blank_) {
// ar[j*w+i] = 0;
ar[j*w+i] = blank_;
}
else {
ar[j*w+i] = scaleValue(value);
}
}
else if (!flag) {
ar[j*w+i] = blank_;
}
}
}
}
/*
* Copy raw image data from this image to the given image data area,
* starting at the image coordinates (x, y) and with the dimentions (w,h)
* in pixels. Since this is a copy from one raw image to another, no
* data conversion is done.
*/
void CLASS_NAME::copyImageArea(void* data, double x, double y, int w, int h)
{
DATA_TYPE* fromImage = (DATA_TYPE*)image_.dataPtr();
DATA_TYPE* toImage = (DATA_TYPE*)data;
int i, j;
int ix, iy;
getIndex(x, y, ix, iy);
for (j = 0; j < h; j++) {
for (i = 0; i < w; i++) {
int rx = ix+i, ry = iy+j;
if (rx >= 0 && ry >= 0 && rx < width_ && ry < height_) {
toImage[j*w+i] = fromImage[ry*width_+rx];
}
else {
toImage[j*w+i] = blank_;
}
}
}
}
/*
* copy the raw image to the xImage
*
* The arguments x0, y0, x1 and y1 are the bounding box of the region of
* the raw image that needs to be copied (origin at upper left (0,0)).
*
* dest_x and dest_y give the coordinates in the XImage where copying
* should start. These are normally either (x0,y0) or (0,0).
*/
void CLASS_NAME::rawToXImage(int x0, int y0, int x1, int y1,
int dest_x, int dest_y)
{
// if (verbose_)
// printf("%s: rawToXImage: %d,%d %d,%d +(%d,%d), flip: %d,%d, rotate: %d\n",
// name_, x0, y0, x1, y1, dest_x, dest_y, flipX_, flipY_, rotate_);
register int i, j;
// row/col increments
register int src_x_inc, src_y_inc;
register int dest_x_inc, dest_y_inc;
// source/dest images
register DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
register int src;
register byte* dest = xImageData_;
initGetVal(); // init flag for speeding up bias subtraction
// width of image area to update
int w = x1 - x0 + 1;
// set loop increments for based on current transformations
switch (flipX_<<1|flipY_) {
case 0: // none
src = (height_ - 1 - y0) * width_ + x0;
src_x_inc = 1;
src_y_inc = -width_ - w;
break;
case 1: // flipY
src = y0 * width_ + x0;
src_x_inc = 1;
src_y_inc = width_ - w;
break;
case 2: // flipX
src = (height_ - 1 - y0) * width_ + (width_ - 1 - x0);
src_x_inc = -1;
src_y_inc = -(width_ - w);
break;
case 3: // flipX and flipY
src = y0 * width_ + (width_ - 1 - x0);
src_x_inc = -1;
src_y_inc = width_ + w;
break;
}
// need to take care with non-byte depths, so branch according to
// this
if ( xImageBytesPerPixel_ == 1 ) {
// set args for rotate in dest image
if (rotate_) {
dest_x_inc = xImageBytesPerLine_;
dest_y_inc = -(w * xImageBytesPerLine_ - 1);
dest += xImageBytesPerLine_ * dest_x + dest_y;
}
else {
dest_x_inc = 1;
dest_y_inc = xImageBytesPerLine_ - w;
dest += xImageBytesPerLine_ * dest_y + dest_x;
}
// copy the raw data to the X image...
for (i=y0; i<=y1; i++) {
for (j=x0; j<=x1; j++) {
*dest = lookup(getVal(rawImage, src));
dest += dest_x_inc;
src += src_x_inc;
}
src += src_y_inc;
dest += dest_y_inc;
}
}
else {
// XImage has depth greater than a byte, need to take care with
// these (byte swapping etc. to server format)
register int k = dest_x;
register int l = dest_y;
for (i=y0; i<=y1; i++) {
for (j=x0; j<=x1; j++) {
if ( rotate_ ) {
xImage_->putpixel( l, k, llookup(getVal(rawImage, src)));
}
else {
xImage_->putpixel( k, l, llookup(getVal(rawImage, src)));
}
src += src_x_inc;
k++;
}
src += src_y_inc;
l++;
k = dest_x;
}
}
}
/*
* This method is called to magnify the image by factors >= 2.
*
* The arguments x0, y0, x1 and y1 are the bounding box of the region
* of the raw image that needs to be copied (origin at upper left (0,0)).
*
* dest_x and dest_y give the coordinates in the XImage where copying
* should start. These are normally either (x0,y0) or (0,0).
*/
void CLASS_NAME::grow(int x0, int y0, int x1, int y1,
int dest_x, int dest_y)
{
register byte *p, *q;
register byte c;
register int i, j, n, m;
register int xs = xScale_, ys = yScale_;
// row/col increments
register int src_x_inc, src_y_inc;
register int dest_x_inc, dest_y_inc;
// source/dest images
register DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
register int src;
register byte* dest = xImageData_;
register byte* end = xImageData_ + xImageSize_;
initGetVal(); // init flag for speeding up bias subtraction
// width of image area to update
int w = x1 - x0 + 1;
// set loop increments based on current transformations
switch (flipX_<<1|flipY_) {
case 0: // none
src = (height_ - 1 - y0) * width_ + x0;
src_x_inc = 1;
src_y_inc = -width_ - w;
break;
case 1: // flipY
src = y0 * width_ + x0;
src_x_inc = 1;
src_y_inc = width_ - w;
break;
case 2: // flipX
src = (height_ - 1 - y0) * width_ + (width_ - 1 - x0);
src_x_inc = -1;
src_y_inc = -(width_ - w);
break;
case 3: // flipX and flipY
src = y0 * width_ + (width_ - 1 - x0);
src_x_inc = -1;
src_y_inc = width_ + w;
break;
}
// need to take care with non-byte depths, so branch according to
// this
if ( xImageBytesPerPixel_ == 1 ) {
// set args for rotate in dest image
if (rotate_) {
dest_x_inc = xImageBytesPerLine_ * xs;
dest_y_inc = -(w * xs * xImageBytesPerLine_ - ys);
dest += xImageBytesPerLine_ * xs * dest_x + dest_y * ys;
}
else {
dest_x_inc = xs;
dest_y_inc = xImageBytesPerLine_ * ys - w * xs;
dest += xImageBytesPerLine_ * ys * dest_y + dest_x * xs;
}
// copy the raw data to the X image...
for (i=y0; i<=y1; i++) {
for (j=x0; j<=x1; j++) {
c = lookup(getVal(rawImage, src));
q = p = dest;
src += src_x_inc;
dest += dest_x_inc;
// replicate the source pixel to an xs x ys box in the dest
for (n=0; n<ys; n++) {
for (m=0; m<xs; m++) {
if (p >= end) {
break;
}
*p++ = c;
}
p = q += xImageBytesPerLine_;
}
}
src += src_y_inc;
dest += dest_y_inc;
}
return;
}
// XImage has depth greater than a byte. Need to take care with
// these (byte swapping etc. to server format, if really
// pushed for performance could use ImageByteOrder() and wing it).
int k = dest_x * xs;
int l = dest_y * ys;
unsigned long cl;
int width;
int height;
if ( rotate_ ) {
height = xImage_->width();
width = xImage_->height();
}
else {
width = xImage_->width();
height = xImage_->height();
}
for ( i = y0; i <= y1; i++ ) {
for ( j = x0; j <= x1; j++ ) {
cl = llookup(getVal(rawImage, src));
// replicate the source pixel to an xs x ys box
int maxN = min(l+ys,height), maxM = min(k+xs,width);
for ( n = l; n < maxN; n++ ) {
for ( m = k; m < maxM; m++ ) {
if ( rotate_ ) {
xImage_->putpixel( n, m, cl );
}
else {
xImage_->putpixel( m, n, cl );
}
}
}
k += xs;
src += src_x_inc;
}
k = dest_x * xs;
l += ys;
src += src_y_inc;
}
}
/*
* This method is called when the image scales require grow and shrink.
*
* The arguments x0, y0, x1 and y1 are the bounding box of the region
* of the raw image that needs to be copied (origin at upper left (0,0)).
*
* dest_x and dest_y give the coordinates in the XImage where copying
* should start. These are normally either (x0,y0) or (0,0).
*/
void CLASS_NAME::growAndShrink(int x0, int y0, int x1, int y1,
int dest_x, int dest_y)
{
register int i, j, n, m;
register int xs = xScale_, ys = yScale_;
register int rxs = xScale_, rys = yScale_;
// One of these is negative, the other not.
if ( xs < 0 ) xs = 1;
if ( ys < 0 ) ys = 1;
// row/col increments
register int src_x_inc, src_y_inc;
// source/dest images
register DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
register int src;
initGetVal(); // init flag for speeding up bias subtraction
// width of image area to update
int w = x1 - x0 + 1;
// set loop increments based on current transformations
switch (flipX_<<1|flipY_) {
case 0: // none
src = (height_ - 1 - y0) * width_ + x0;
src_x_inc = 1;
src_y_inc = -width_ - w;
break;
case 1: // flipY
src = y0 * width_ + x0;
src_x_inc = 1;
src_y_inc = width_ - w;
break;
case 2: // flipX
src = (height_ - 1 - y0) * width_ + (width_ - 1 - x0);
src_x_inc = -1;
src_y_inc = -(width_ - w);
break;
case 3: // flipX and flipY
src = y0 * width_ + (width_ - 1 - x0);
src_x_inc = -1;
src_y_inc = width_ + w;
break;
}
int k = dest_x * xs;
int l = dest_y * ys;
unsigned long cl;
int width;
int height;
if ( rotate_ ) {
height = xImage_->width();
width = xImage_->height();
}
else {
width = xImage_->width();
height = xImage_->height();
}
// For the axis that is shrank, we need to stop the pick for a number of
// times that gets a step along that axis of the right number.
int yskip = 0;
int xskip = 0;
if ( rys < 0 ) {
yskip = -rys;
}
if ( rxs < 0 ) {
xskip = -rxs;
}
// Skip counters.
int xc = 0;
int yc = 0;
for ( i = y0; i <= y1; i++ ) {
xc = 0;
for ( j = x0; j <= x1; j++ ) {
cl = llookup(getVal(rawImage, src));
// replicate the source pixel to an xs x ys box
int maxN = min(l+ys,height), maxM = min(k+xs,width);
for ( n = l; n < maxN; n++ ) {
for ( m = k; m < maxM; m++ ) {
if ( rotate_ ) {
xImage_->putpixel( n, m, cl );
}
else {
xImage_->putpixel( m, n, cl );
}
}
}
// When xScale_ < 0 need to use same pixel again...
xc++;
if ( xc >= xskip ) {
k += xs;
xc = 0;
}
src += src_x_inc;
}
k = dest_x * xs;
// When yScale_ < 0 need to use same pixel again...
yc++;
if ( yc >= yskip ) {
l += ys;
yc = 0;
}
src += src_y_inc;
}
}
/*
* get samples of a square box
* rawImage : input array
* idx : offset in array
* wbox : width of box
* samples : output vector
* returns the number of pixels in the output array samples
*/
inline int CLASS_NAME::getBsamples(DATA_TYPE *rawImage, int idx, int wbox, DATA_TYPE *samples)
{
int i, k, src;
for (k = 0; k < wbox; k++) {
src = idx + k * width_;
for (i = 0; i < wbox; i++) {
*samples++ = getVal(rawImage, src++);
}
}
return (wbox * wbox);
}
/*
* get samples of a square box (only "black" values on chess-board)
* rawImage : input array
* idx : offset in array
* wbox : width of box
* samples : output vector
* returns the number of pixels in the output array samples
*/
inline int CLASS_NAME::getCsamples(DATA_TYPE *rawImage, int idx, int wbox, DATA_TYPE *samples)
{
int i, k, src;
for (k = 0; k < wbox; k++) {
src = idx + k * width_ + k%2;
for (i = 0; i < wbox; i += 2) {
*samples++ = getVal(rawImage, src+i);
}
}
return ((wbox * wbox) / 2 + wbox%2);
}
/*
* get samples on a diagonal cross of a square box
* rawImage : input array
* idx : offset in array
* wbox : width of box
* samples : output vector
* returns the number of pixels in the output array samples
*/
inline int CLASS_NAME::getXsamples(DATA_TYPE *rawImage, int idx, int wbox, DATA_TYPE *samples)
{
int i, n = 0, m = wbox/2;
int offs = wbox -1;
int idxo = idx + offs;
int woff = width_ * offs;
if (wbox %2 != 0) {
n++;
*samples++ = getVal(rawImage, idx + width_ * m + m); /* center pixel of cross */
}
for (i = 0; i < m; i++) {
*samples++ = getVal(rawImage, idx);
*samples++ = getVal(rawImage, idxo);
*samples++ = getVal(rawImage, idx + woff);
*samples++ = getVal(rawImage, idxo + woff);
idx += width_ + 1;
offs -= 2;
idxo = idx + offs;
woff = width_ * offs;
}
return (n + m * 4);
}
/*
* get median value of array samples
* samples : data vector
* n : number of pixels in vector samples
* returns the median value of vector samples
*/
inline DATA_TYPE CLASS_NAME::getMedian(DATA_TYPE *samples, int n)
{
int i, k;
DATA_TYPE *pi, *pk = samples, tmp;
for (k = 0; k < n; k++, pk++) {
pi = samples + k+1;
for (i = k+1; i < n; i++, pi++) {
if (*pk < *pi) {
tmp = *pk;
*pk = *pi;
*pi = tmp;
}
}
}
return (*(samples + n/2));
}
/*
* get RMS value of array samples
* samples : data vector
* n : number of pixels in vector samples
* returns the RMS value of vector samples
*/
inline DATA_TYPE CLASS_NAME::getRMS(DATA_TYPE *samples, int n)
{
int i, cnt = 0;
double sum = 0.0, sumsq = 0.0;
DATA_TYPE value;
for (i = 0; i < n; i++) {
value = *samples++;
cnt++;
sumsq += value * value;
sum += value;
}
if (cnt < 2)
return ((DATA_TYPE) 0);
value = (DATA_TYPE)sqrt((sumsq - ((sum * sum) / cnt)) / (cnt -1));
return (value);
}
/*
* get value of a shrunk image which is not subsampled
* rawImage : input array
* idx : offset in array
* wbox : width of box
* samples : allocated temporary array
* xs : scale factor
* returns the value according to the sampling method
*/
inline DATA_TYPE CLASS_NAME::getBoxVal(DATA_TYPE *rawImage, int idx, int wbox, DATA_TYPE *samples, int xs)
{
DATA_TYPE value;
DATA_TYPE *psamples = samples;
int n, m;
double sum;
switch (sampmethod_) {
case SAMP_METHOD_MIN:
m = getBsamples(rawImage, idx, wbox, samples);
for (n = 1, value = *psamples++; n < m; n++, psamples++) {
if (*psamples < value)
value = *psamples;
}
return (value);
case SAMP_METHOD_MEAN:
m = getBsamples(rawImage, idx, wbox, samples);
for (n = 0, sum = 0.0; n < m; n++) {
sum += *psamples++;
}
return ((DATA_TYPE) (sum / m));
case SAMP_METHOD_MEDIAN:
m = getBsamples(rawImage, idx, wbox, samples);
return (getMedian(samples, m));
case SAMP_METHOD_RMS:
m = getBsamples(rawImage, idx, wbox, samples);
return ((DATA_TYPE)getRMS(samples, m));
case SAMP_METHOD_MAX_CROSS:
m = getXsamples(rawImage, idx, wbox, samples);
for (n = 1, value = *psamples++; n < m; n++, psamples++) {
if (*psamples > value)
value = *psamples;
}
return (value);
case SAMP_METHOD_MIN_CROSS:
m = getXsamples(rawImage, idx, wbox, samples);
for (n = 1, value = *psamples++; n < m; n++, psamples++) {
if (*psamples < value)
value = *psamples;
}
return (value);
case SAMP_METHOD_MEAN_CROSS:
m = getXsamples(rawImage, idx, wbox, samples);
for (n = 0, sum = 0.0; n < m; n++) {
sum += *psamples++;
}
return ((DATA_TYPE) (sum / m));
case SAMP_METHOD_MEDIAN_CROSS:
m = getXsamples(rawImage, idx, wbox, samples);
return (getMedian(samples, m));
case SAMP_METHOD_MEDIAN_CHESS:
m = getCsamples(rawImage, idx, wbox, samples);
return (getMedian(samples, m));
case SAMP_METHOD_MEDIAN_9:
wbox = (xs < 3) ? 1 : 3;
m = getBsamples(rawImage, idx, wbox, samples);
return (getMedian(samples, m));
default: /* SAMP_METHOD_MAX */
m = getBsamples(rawImage, idx, wbox, samples);
for (n = 1, value = *psamples++; n < m; n++, psamples++) {
if (*psamples > value)
value = *psamples;
}
return (value);
}
return (0);
}
/*
* This method is called to shrink the image. If subsample_ is 1, just
* take every nth pixel as a sample, otherwise take the max of the
* surrounding pixels
*
* The arguments x0, y0, x1 and y1 are the bounding box of the region
* of the raw image that needs to be copied (origin at upper left (0,0)).
*
* dest_x and dest_y give the coordinates in the XImage where copying
* should start. These are normally either (x0,y0) or (0,0).
*
* Note: there is a (non-fatal) bug here that shows up when dest_x,dest_y are non-zero,
* (the image display gets split or mixed up somehow...) - needs some
* testing to see what the cause is.
*/
void CLASS_NAME::shrink(int x0, int y0, int x1, int y1, int dest_x, int dest_y)
{
int p=0, q=0;
int i, j, n, m;
int xs = -xScale_, ys = -yScale_;
initGetVal(); // init flag for speeding up bias subtraction
// for odd shrink factors, we have to be carefull about the end conditions
x1 -= (x1-x0+1)%xs;
y1 -= (y1-y0+1)%ys;
int w = x1-x0+1;
// row/col increments
int src_x_inc, src_y_inc;
int dest_x_inc, dest_y_inc;
// source/dest images
DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
int src;
byte* dest = xImageData_;
byte* end = xImageData_ + xImageSize_ - 1;
DATA_TYPE maxval = 0;
// set loop increments based on current transformations
switch (flipX_<<1|flipY_) {
case 0: // none
src = (height_ - ys - y0) * width_ + x0;
src_x_inc = xs;
src_y_inc = -width_ * ys - w;
break;
case 1: // flipY
src = y0 * width_ + x0;
src_x_inc = xs;
src_y_inc = width_ * ys - w;
break;
case 2: // flipX
src = (height_ - ys - y0) * width_ + (width_ - xs - x0);
src_x_inc = -xs;
src_y_inc = -(width_ * ys - w);
break;
case 3: // flipX and flipY
src = y0 * width_ + (width_ - xs - x0);
src_x_inc = -xs;
src_y_inc = width_ * ys + w;
break;
}
if ( xImageBytesPerPixel_ == 1 ) {
// use faster methods for byte xImages
// set args for rotate in dest image
if (rotate_) {
dest_x_inc = xImageBytesPerLine_;
dest_y_inc = -(w/xs * xImageBytesPerLine_ - 1);
dest += xImageBytesPerLine_ * (dest_x/xs) + (dest_y/ys);
}
else {
dest_x_inc = 1;
dest_y_inc = xImageBytesPerLine_ - w/xs;
dest += xImageBytesPerLine_ * (dest_y/ys) + (dest_x/xs);
}
// copy the raw data to the X image...
if (subsample_) {
// use faster "subsample" algorithm
for (i=y0; i<=y1; i+=ys) {
for (j=x0; j<=x1; j+=xs) {
if (dest > end) {
break;
}
*dest = lookup(getVal(rawImage, src));
dest += dest_x_inc;
src += src_x_inc;
}
src += src_y_inc;
dest += dest_y_inc;
}
}
else {
// don't subsample: take max pixel
for (i=y0; i<=y1; i+=ys) {
for (j=x0; j<=x1; j+=xs) {
if (dest > end) {
break;
}
q = p = src;
for (n=0; n<ys; n++) {
for (m=0; m<xs; m++, p++) {
if (getVal(rawImage, p) > maxval)
maxval = getVal(rawImage, p);
}
p = q += width_;
}
*dest = lookup(maxval);
maxval = 0;
dest += dest_x_inc;
src += src_x_inc;
}
src += src_y_inc;
dest += dest_y_inc;
}
}
return;
}
// XImage depth greater than a byte. Use careful methods to
// keep byte order etc. correct for server.
int k = dest_x / xs;
int l = dest_y / ys;
if (subsample_ || xs < 2 || ys < 2) {
// use faster "subsample" algorithm
for (i=y0; i<=y1; i+=ys) {
for (j=x0; j<=x1; j+=xs) {
if ( rotate_ ) {
xImage_->putpixel( l, k, llookup(getVal(rawImage, src)));
}
else {
xImage_->putpixel( k, l, llookup(getVal(rawImage, src)));
}
k++;
src += src_x_inc;
}
src += src_y_inc;
k = dest_x / xs;
l++;
}
return;
}
// don't subsample: take pixel defined by sampling method
DATA_TYPE *samples = new DATA_TYPE[xs * ys];
DATA_TYPE vsamp;
int wbox = xs < ys ? xs : ys;
for (i = y0; i < y1; i += ys, src += src_y_inc, k = dest_x / xs, l++) {
for (j = x0; j < x1; j += xs, src += src_x_inc) {
vsamp = getBoxVal(rawImage, src, wbox, samples, xs);
if ( rotate_ )
xImage_->putpixel(l, k++, llookup(vsamp));
else
xImage_->putpixel(k++, l, llookup(vsamp));
}
}
delete[] samples;
}
/*
* Set the cut levels using a median filtering algorithm.
* To save time, only a center area of the visible image is examined.
*/
void CLASS_NAME::medianFilter()
{
getMinMax(); // get min/max pixel estimate for visible area
DATA_TYPE *rawImage = (DATA_TYPE*)image_.dataPtr(); // image data
const int nmed = 7; // length of median filter
int xskip = nmed*3, yskip = 3; // skip pixels for speed
int x0 = x0_ + 10; // ignore outside areas
int y0 = y0_ + 10;
int x1 = x1_ - 10;
int y1 = y1_ - 10;
int i, j, k, l;
int p=0;
DATA_TYPE tmp;
DATA_TYPE val, lcut, hcut, medary[nmed];
// use this value as a default in place of bad pixels (blank, NAN)
DATA_TYPE mval = (DATA_TYPE)((minValue_ + maxValue_)/2);
initGetVal(); // init flag for speeding up bias subtraction
if (x1-x0 <= nmed || y1-y0 <= nmed)
return;
for (i=y0; i<=y1; i+=yskip) {
for (j=x0; j<=x1; j+=xskip) {
p = i*width_ + j;
// get array for finding meadian
for (k=0; k < nmed; k++) {
medary[k] = getVal(rawImage, p++);
// ignore blank pixels and NANs
if (ISNAN(medary[k]) || (haveBlank_ && medary[k] == blank_)) {
medary[k] = mval;
}
}
// get median value
for (k=0; k < nmed; k++) {
for (l=k; l < nmed; l++) {
if (medary[k] < medary[l]) {
tmp = medary[l];
medary[l] = medary[k];
medary[k] = tmp;
}
}
}
val = medary[nmed/2];
if ( val == mval ) {
if ( i == y0 ) {
lcut = hcut = 0; // To be safe.
}
continue; // PWD: Skip runs of blank pixels.
}
if (i == y0)
// set initial low and high cut values
lcut = hcut = val;
else {
// compare meadian with lcut, hcut
if (val < lcut)
lcut = val;
if (val > hcut)
hcut = val;
}
}
}
setCutLevels(lcut, hcut, 0);
}
/*
* Fill the given array (xyvalues) with statistics about the distribution
* of pixels in the visible image area (given by x0_, y0_, x1_, y1_).
* xyvalues[n*2+1] is set to the number of pixels with value at or near n.
* The factor is used to fit the information in the given size aray.
*/
void CLASS_NAME::getPixDist(int numValues, double* xyvalues, double factor)
{
DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
DATA_TYPE mv = (DATA_TYPE)minValue_;
DATA_TYPE value;
initGetVal(); // init flag for speeding up bias subtraction
// the Y values are the number of pixels in a given range
// note: to save time, don't check all the pixels, just a
// number of sample lines in the visible area of the image.
if (x1_ <= x0_ || y1_ <= y0_)
return;
for (int i=y0_; i<y1_; i++) {
for (int j=x0_; j<x1_; j++) {
// the code below converts an image pixel value to an index
// in the xyvalues array, so that we can increment the count for
// that pixel value range. The array is numValues*2 long, since
// for each pixel value, the value and the count are stored.
value = getVal(rawImage, i*width_+j);
if (ISNAN(value) || (haveBlank_ && value == blank_))
continue;
int idx = int((value-mv)/factor);
if (idx >= 0 && idx < numValues)
xyvalues[idx*2+1]++;
}
}
}
/*
* Fill the given histogram with the distribution of pixels in the
* visible image area (given by x0_, y0_, x1_, y1_). h.histogram[n] is
* set to the number of pixels with a value of n (after conversion to
* short if needed).
*/
void CLASS_NAME::getHistogram(ImageDataHistogram& hist)
{
DATA_TYPE* rawImage = (DATA_TYPE*)image_.dataPtr();
DATA_TYPE value;
initGetVal(); // init flag for speeding up bias subtraction
// if we are looking at the whole image, ignore the margin
int w = x1_ - x0_ + 1, h = y1_ - y0_ + 1;
int xmargin = 0, ymargin = 0;
if (w == width_)
xmargin = int(w * 0.2);
if (y0_ == 0)
ymargin = int(h * 0.2);
int x0 = x0_ + xmargin;
int y0 = y0_ + ymargin;
int x1 = x1_ - xmargin;
int y1 = y1_ - ymargin;
// the array values are the number of pixels in a given range
// note: to save time, don't check all the pixels, just a
// number of sample lines in the visible area of the image.
if (x1 <= x0 || y1 <= y0) {
hist.area = 0;
return;
}
hist.area = (x1 - x0) * (y1 - y0);
for (int i=y0; i<y1; i++) {
for (int j=x0; j<x1; j++) {
// the code below converts an image pixel value to short and then
// uses it to index in the histogram array, so that we can increment the
// count for that pixel value.
value = getVal(rawImage, i*width_+j);
if (ISNAN(value) || (haveBlank_ && value == blank_))
continue;
hist.histogram[convertToUshort(value)]++;
}
}
}
/*
* If there is a special value for blank pixels, get it.
*
* Note that the blank pixel value is not scaled by bscale, since we
* compare pixels values with this value before scaling.
*/
void CLASS_NAME::initBlankPixel()
{
// If an override for the BLANK value exists, use it.
if ( blankValue_[0] != '\0' ) {
haveBlank_ = parseBlank( blankValue_ );
}
if (!haveBlank_) {
haveBlank_ = (image_.get("BLANK", blank_) == 0);
if (!haveBlank_)
haveBlank_ = (image_.get("BADPIXEL", blank_) == 0);
}
}
#undef ISNAN
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