void is_decode(ic_stream *ics, ic_stream *icsr, real_t *l_spec, real_t *r_spec,
uint16_t frame_len)
{
uint8_t g, sfb, b;
uint16_t i;
#ifndef FIXED_POINT
real_t scale;
#else
int32_t exp, frac;
#endif
uint16_t nshort = frame_len/8;
uint8_t group = 0;
for (g = 0; g < icsr->num_window_groups; g++)
{
/* Do intensity stereo decoding */
for (b = 0; b < icsr->window_group_length[g]; b++)
{
for (sfb = 0; sfb < icsr->max_sfb; sfb++)
{
if (is_intensity(icsr, g, sfb))
{
/* For scalefactor bands coded in intensity stereo the
corresponding predictors in the right channel are
switched to "off".
*/
ics->pred.prediction_used[sfb] = 0;
icsr->pred.prediction_used[sfb] = 0;
#ifndef FIXED_POINT
scale = (real_t)pow(0.5, (0.25*icsr->scale_factors[g][sfb]));
#else
exp = icsr->scale_factors[g][sfb] >> 2;
frac = icsr->scale_factors[g][sfb] & 3;
#endif
/* Scale from left to right channel,
do not touch left channel */
for (i = icsr->swb_offset[sfb]; i < icsr->swb_offset[sfb+1]; i++)
{
#ifndef FIXED_POINT
r_spec[(group*nshort)+i] = MUL_R(l_spec[(group*nshort)+i], scale);
#else
if (exp < 0)
r_spec[(group*nshort)+i] = l_spec[(group*nshort)+i] << -exp;
else
r_spec[(group*nshort)+i] = l_spec[(group*nshort)+i] >> exp;
r_spec[(group*nshort)+i] = MUL_C(r_spec[(group*nshort)+i], pow05_table[frac + 3]);
#endif
if (is_intensity(icsr, g, sfb) != invert_intensity(ics, g, sfb))
r_spec[(group*nshort)+i] = -r_spec[(group*nshort)+i];
}
}
}
group++;
}
}
}
void GUI::apply_filter_from_menu(Controller &controller, Gtk::ImageMenuItem &imagemenuitem) {
if ( ! controller.image_file_loaded ) { return ; }
bool is_alpha = controller.current_image_to_process.channels() == 4 ;
Sharpen sharpen_filter(3, "diamond") ;
Sharpen sharpen_filter_more(3, "diamond") ;
Find_Edges find_edges_filter(3) ;
Mean mean_filter(3) ;
Mean mean_filter_more(5) ;
cv::Mat kernel = make_kernel("rect", 3) ;
cv::Mat tmp = controller.current_image_to_process.clone() ;
cv::Mat frame ;
switch ( stoi(imagemenuitem.get_name()) ) {
case 0 :
// Pencil Sketch filter.
pencil_sketch_filter(tmp, frame) ;
break ;
case 1 :
// Stylisation filter.
stylisation_filter(tmp, frame) ;
break ;
case 2 :
// Detail Enhance filter.
detail_enhance_filter(tmp, frame) ;
break ;
case 3 :
// Edge Preserving filter.
edge_preserving_filter(tmp, frame) ;
break ;
case 4 :
// Stroke edges filter:
stroke_edges(tmp, frame) ;
break ;
case 5 :
// Invert Intensity filter:
invert_intensity(tmp, frame) ;
break ;
case 6 :
// Light Intensity filter:
effect_light(tmp, frame) ;
break ;
case 7 :
// Recolor-RC (Red-Cyan) filter:
recolorRC(tmp, frame) ;
break ;
case 8 :
// Recolor-RC (Red-Green-Value) filter:
recolorRGV(tmp, frame) ;
break ;
case 9 :
// Recolor-RC (Cyan-Magenta-Value) filter:
recolorCMV(tmp, frame) ;
break ;
case 10 :
// Extrema Maximal Filter:
extrema(tmp, frame, "max") ;
break ;
case 11 :
// Extrema Minimal Filter:
extrema(tmp, frame, "min") ;
break ;
case 12 :
// Sharpen filter:
sharpen_filter.apply(tmp, frame) ;
break ;
case 13 :
// Sharpen More filter:
sharpen_filter_more.apply(tmp, frame) ;
break ;
case 14 :
// Find Edges filter:
if (is_alpha) {
cv::Mat frame_rgb ;
cv::Mat tmp_1 ;
cvtColor(tmp, frame_rgb, cv::COLOR_BGRA2BGR) ;
find_edges_filter.apply(frame_rgb, tmp_1) ;
vector<cv::Mat> tmp_2 ;
vector<cv::Mat> tmp_3 ;
cv::split(tmp, tmp_2) ;
cv::split(tmp_1, tmp_3) ;
// Assign BGR channels.
tmp_2[0] = tmp_3[0] ;
tmp_2[1] = tmp_3[1] ;
tmp_2[2] = tmp_3[2] ;
// Final channels merging into result with alpha channel unchanged.
cv::merge(tmp_2, frame) ;
break ;
}
find_edges_filter.apply(tmp, frame) ;
break ;
case 15 :
// Mean Blur filter:
mean_filter.apply(tmp, frame) ;
break ;
case 16 :
// Mean Blur More filter:
mean_filter_more.apply(tmp, frame) ;
break ;
case 17 :
// Blur filter:
blur_filter(tmp, frame) ;
break ;
case 18 :
// Median Blur filter:
median_blur_filter(tmp, frame) ;
break ;
case 19 :
// Gaussian Blur filter:
gaussian_blur_filter(tmp, frame) ;
break ;
case 20 :
denoising_filter(tmp, frame) ;
break ;
case 21 :
// Erode filter:
erode_filter(tmp, frame, kernel, 1) ;
break ;
case 22 :
// Dilate filter:
dilate_filter(tmp, frame, kernel, 1) ;
break ;
case 23 :
// Wave Horizontally filter:
wave(tmp, frame, -1) ;
break ;
case 24 :
// Wave Vertically filter:
wave(tmp, frame, 1) ;
break ;
case 25 :
// Wave Twice (Horizontally and Vertically) filter:
wave(tmp, frame, 0) ;
break ;
case 26 :
// Contours Sobel White filter.
sobel_drawning(tmp, frame, 3, false, 1) ;
break ;
case 27 :
// Contours Sobel Black filter.
sobel_drawning(tmp, frame, 3, false, -1) ;
break ;
case 28 :
// Contours Sobel Emboss filter.
sobel_drawning(tmp, frame, 3, false, 0) ;
break ;
case 29 :
// Emboss Sobel filter:
sobel_emboss(tmp, frame, 3) ;
break ;
case 30 :
// Emboss Laplacian filter:
laplacian_emboss(tmp, frame, 3) ;
break ;
case 31 :
// Binary White OTSU filter:
// Build a binary image (a black and white only image) with white background (@arg value true)
// based on the OTSU threshold computing algorithm (@arg value -1).
build_binary_image(tmp, frame, -1, true) ;
break ;
case 32 :
// Binary White TRIANGLE filter:
// Build a binary image (a black and white only image) with white background (@arg value true)
// based on the TRIANGLE threshold computing algorithm (@arg value 1).
build_binary_image(tmp, frame, 1, true) ;
break ;
case 33 :
// Binary White AVERAGE filter:
// Build a binary image (a black and white only image) with white background (@arg value true)
// based on the AVERAGE threshold from OTSU and TRIANGLE (@arg value 0).
build_binary_image(tmp, frame, 0, true) ;
break ;
case 34 :
// Binary Black OTSU filter:
// Build a binary image (a black and white only image) with black background (@arg value true)
// based on the OTSU threshold computing algorithm (@arg value -1).
build_binary_image(tmp, frame, -1, false) ;
break ;
case 35 :
// Binary Black TRIANGLE filter:
// Build a binary image (a black and white only image) with black background (@arg value true)
// based on the TRIANGLE threshold computing algorithm (@arg value 1).
build_binary_image(tmp, frame, 1, false) ;
break ;
case 36 :
// Binary Black AVERAGE filter:
// Build a binary image (a black and white only image) with black background (@arg value true)
// based on the AVERAGE threshold from OTSU and TRIANGLE (@arg value 0).
build_binary_image(tmp, frame, 0, false) ;
break ;
case 37 :
// Binary Contours White filter:
// Build a binary image (a black and white only image) with contours detction on white background (@arg value false).
laplacian_zero_crossing(tmp, frame, 19, false) ;
break ;
case 38 :
// Binary Contours Black filter:
// Build a binary image (a black and white only image) with contours detction on black background (@arg value true).
laplacian_zero_crossing(tmp, frame, 19, true) ;
break ;
#ifdef DEBUG
default :
// Cannot append due of the GUI interfacing.
fprintf(stdout,"Error applying filter !!!\n") ;
return ;
#endif
}
// We register current frame in vector<cv::Mat> for undo-redo.
controller.process_after_applying(frame) ;
// It convert current_image_to_process as src to RGB(A) in dst current_image_to_display.
set_img(frame, controller.current_image_to_display, controller) ; // It auto process conversion to RGB(A).
// Reset some variables.
after_applying_reset_settings(controller) ;
}
