FFmpeg coverage


Directory: ../../../ffmpeg/
File: src/libavfilter/vf_vaguedenoiser.c
Date: 2022-11-26 13:19:19
Exec Total Coverage
Lines: 0 280 0.0%
Branches: 0 136 0.0%

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1 /*
2 * Copyright (c) 2003 LeFunGus, lefungus@altern.org
3 *
4 * This file is part of FFmpeg
5 *
6 * FFmpeg is free software; you can redistribute it and/or modify
7 * it under the terms of the GNU General Public License as published by
8 * the Free Software Foundation; either version 2 of the License, or
9 * (at your option) any later version.
10 *
11 * FFmpeg is distributed in the hope that it will be useful,
12 * but WITHOUT ANY WARRANTY; without even the implied warranty of
13 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
14 * GNU General Public License for more details.
15 *
16 * You should have received a copy of the GNU General Public License along
17 * with FFmpeg; if not, write to the Free Software Foundation, Inc.,
18 * 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
19 */
20
21 #include <float.h>
22
23 #include "libavutil/imgutils.h"
24 #include "libavutil/attributes.h"
25 #include "libavutil/common.h"
26 #include "libavutil/pixdesc.h"
27 #include "libavutil/intreadwrite.h"
28 #include "libavutil/opt.h"
29
30 #include "avfilter.h"
31 #include "formats.h"
32 #include "internal.h"
33 #include "video.h"
34
35 typedef struct VagueDenoiserContext {
36 const AVClass *class;
37
38 float threshold;
39 float percent;
40 int method;
41 int type;
42 int nsteps;
43 int planes;
44
45 int depth;
46 int bpc;
47 int peak;
48 int nb_planes;
49 int planeheight[4];
50 int planewidth[4];
51
52 float *block;
53 float *in;
54 float *out;
55 float *tmp;
56
57 int hlowsize[4][32];
58 int hhighsize[4][32];
59 int vlowsize[4][32];
60 int vhighsize[4][32];
61
62 void (*thresholding)(float *block, const int width, const int height,
63 const int stride, const float threshold,
64 const float percent);
65 } VagueDenoiserContext;
66
67 #define OFFSET(x) offsetof(VagueDenoiserContext, x)
68 #define FLAGS AV_OPT_FLAG_VIDEO_PARAM | AV_OPT_FLAG_FILTERING_PARAM
69 static const AVOption vaguedenoiser_options[] = {
70 { "threshold", "set filtering strength", OFFSET(threshold), AV_OPT_TYPE_FLOAT, {.dbl=2.}, 0,DBL_MAX, FLAGS },
71 { "method", "set filtering method", OFFSET(method), AV_OPT_TYPE_INT, {.i64=2 }, 0, 2, FLAGS, "method" },
72 { "hard", "hard thresholding", 0, AV_OPT_TYPE_CONST, {.i64=0}, 0, 0, FLAGS, "method" },
73 { "soft", "soft thresholding", 0, AV_OPT_TYPE_CONST, {.i64=1}, 0, 0, FLAGS, "method" },
74 { "garrote", "garrote thresholding", 0, AV_OPT_TYPE_CONST, {.i64=2}, 0, 0, FLAGS, "method" },
75 { "nsteps", "set number of steps", OFFSET(nsteps), AV_OPT_TYPE_INT, {.i64=6 }, 1, 32, FLAGS },
76 { "percent", "set percent of full denoising", OFFSET(percent),AV_OPT_TYPE_FLOAT, {.dbl=85}, 0,100, FLAGS },
77 { "planes", "set planes to filter", OFFSET(planes), AV_OPT_TYPE_INT, {.i64=15 }, 0, 15, FLAGS },
78 { "type", "set threshold type", OFFSET(type), AV_OPT_TYPE_INT, {.i64=0 }, 0, 1, FLAGS, "type" },
79 { "universal", "universal (VisuShrink)", 0, AV_OPT_TYPE_CONST, {.i64=0}, 0, 0, FLAGS, "type" },
80 { "bayes", "bayes (BayesShrink)", 0, AV_OPT_TYPE_CONST, {.i64=1}, 0, 0, FLAGS, "type" },
81 { NULL }
82 };
83
84 AVFILTER_DEFINE_CLASS(vaguedenoiser);
85
86 #define NPAD 10
87
88 static const float analysis_low[9] = {
89 0.037828455506995f, -0.023849465019380f, -0.110624404418423f, 0.377402855612654f,
90 0.852698679009403f, 0.377402855612654f, -0.110624404418423f, -0.023849465019380f, 0.037828455506995f
91 };
92
93 static const float analysis_high[7] = {
94 -0.064538882628938f, 0.040689417609558f, 0.418092273222212f, -0.788485616405664f,
95 0.418092273222212f, 0.040689417609558f, -0.064538882628938f
96 };
97
98 static const float synthesis_low[7] = {
99 -0.064538882628938f, -0.040689417609558f, 0.418092273222212f, 0.788485616405664f,
100 0.418092273222212f, -0.040689417609558f, -0.064538882628938f
101 };
102
103 static const float synthesis_high[9] = {
104 -0.037828455506995f, -0.023849465019380f, 0.110624404418423f, 0.377402855612654f,
105 -0.852698679009403f, 0.377402855612654f, 0.110624404418423f, -0.023849465019380f, -0.037828455506995f
106 };
107
108 static const enum AVPixelFormat pix_fmts[] = {
109 AV_PIX_FMT_GRAY8, AV_PIX_FMT_GRAY9, AV_PIX_FMT_GRAY10,
110 AV_PIX_FMT_GRAY12, AV_PIX_FMT_GRAY14, AV_PIX_FMT_GRAY16,
111 AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P,
112 AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P,
113 AV_PIX_FMT_YUV440P, AV_PIX_FMT_YUV444P,
114 AV_PIX_FMT_YUVJ420P, AV_PIX_FMT_YUVJ422P,
115 AV_PIX_FMT_YUVJ440P, AV_PIX_FMT_YUVJ444P,
116 AV_PIX_FMT_YUVJ411P,
117 AV_PIX_FMT_YUV420P9, AV_PIX_FMT_YUV422P9, AV_PIX_FMT_YUV444P9,
118 AV_PIX_FMT_YUV420P10, AV_PIX_FMT_YUV422P10, AV_PIX_FMT_YUV444P10,
119 AV_PIX_FMT_YUV440P10,
120 AV_PIX_FMT_YUV444P12, AV_PIX_FMT_YUV422P12, AV_PIX_FMT_YUV420P12,
121 AV_PIX_FMT_YUV440P12,
122 AV_PIX_FMT_YUV444P14, AV_PIX_FMT_YUV422P14, AV_PIX_FMT_YUV420P14,
123 AV_PIX_FMT_YUV420P16, AV_PIX_FMT_YUV422P16, AV_PIX_FMT_YUV444P16,
124 AV_PIX_FMT_GBRP, AV_PIX_FMT_GBRP9, AV_PIX_FMT_GBRP10,
125 AV_PIX_FMT_GBRP12, AV_PIX_FMT_GBRP14, AV_PIX_FMT_GBRP16,
126 AV_PIX_FMT_YUVA420P, AV_PIX_FMT_YUVA422P, AV_PIX_FMT_YUVA444P,
127 AV_PIX_FMT_YUVA444P9, AV_PIX_FMT_YUVA444P10, AV_PIX_FMT_YUVA444P12, AV_PIX_FMT_YUVA444P16,
128 AV_PIX_FMT_YUVA422P9, AV_PIX_FMT_YUVA422P10, AV_PIX_FMT_YUVA422P12, AV_PIX_FMT_YUVA422P16,
129 AV_PIX_FMT_YUVA420P9, AV_PIX_FMT_YUVA420P10, AV_PIX_FMT_YUVA420P16,
130 AV_PIX_FMT_GBRAP, AV_PIX_FMT_GBRAP10, AV_PIX_FMT_GBRAP12, AV_PIX_FMT_GBRAP16,
131 AV_PIX_FMT_NONE
132 };
133
134 static int config_input(AVFilterLink *inlink)
135 {
136 VagueDenoiserContext *s = inlink->dst->priv;
137 const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format);
138 int p, i, nsteps_width, nsteps_height, nsteps_max;
139
140 s->depth = desc->comp[0].depth;
141 s->bpc = (s->depth + 7) / 8;
142 s->nb_planes = desc->nb_components;
143
144 s->planeheight[1] = s->planeheight[2] = AV_CEIL_RSHIFT(inlink->h, desc->log2_chroma_h);
145 s->planeheight[0] = s->planeheight[3] = inlink->h;
146 s->planewidth[1] = s->planewidth[2] = AV_CEIL_RSHIFT(inlink->w, desc->log2_chroma_w);
147 s->planewidth[0] = s->planewidth[3] = inlink->w;
148
149 s->block = av_malloc_array(inlink->w * inlink->h, sizeof(*s->block));
150 s->in = av_malloc_array(32 + FFMAX(inlink->w, inlink->h), sizeof(*s->in));
151 s->out = av_malloc_array(32 + FFMAX(inlink->w, inlink->h), sizeof(*s->out));
152 s->tmp = av_malloc_array(32 + FFMAX(inlink->w, inlink->h), sizeof(*s->tmp));
153
154 if (!s->block || !s->in || !s->out || !s->tmp)
155 return AVERROR(ENOMEM);
156
157 s->threshold *= 1 << (s->depth - 8);
158 s->peak = (1 << s->depth) - 1;
159
160 nsteps_width = ((s->planes & 2 || s->planes & 4) && s->nb_planes > 1) ? s->planewidth[1] : s->planewidth[0];
161 nsteps_height = ((s->planes & 2 || s->planes & 4) && s->nb_planes > 1) ? s->planeheight[1] : s->planeheight[0];
162
163 for (nsteps_max = 1; nsteps_max < 15; nsteps_max++) {
164 if (pow(2, nsteps_max) >= nsteps_width || pow(2, nsteps_max) >= nsteps_height)
165 break;
166 }
167
168 s->nsteps = FFMIN(s->nsteps, nsteps_max - 2);
169
170 for (p = 0; p < 4; p++) {
171 s->hlowsize[p][0] = (s->planewidth[p] + 1) >> 1;
172 s->hhighsize[p][0] = s->planewidth[p] >> 1;
173 s->vlowsize[p][0] = (s->planeheight[p] + 1) >> 1;
174 s->vhighsize[p][0] = s->planeheight[p] >> 1;
175
176 for (i = 1; i < s->nsteps; i++) {
177 s->hlowsize[p][i] = (s->hlowsize[p][i - 1] + 1) >> 1;
178 s->hhighsize[p][i] = s->hlowsize[p][i - 1] >> 1;
179 s->vlowsize[p][i] = (s->vlowsize[p][i - 1] + 1) >> 1;
180 s->vhighsize[p][i] = s->vlowsize[p][i - 1] >> 1;
181 }
182 }
183
184 return 0;
185 }
186
187 static inline void copy(const float *p1, float *p2, const int length)
188 {
189 memcpy(p2, p1, length * sizeof(float));
190 }
191
192 static inline void copyv(const float *p1, const int stride1, float *p2, const int length)
193 {
194 int i;
195
196 for (i = 0; i < length; i++) {
197 p2[i] = *p1;
198 p1 += stride1;
199 }
200 }
201
202 static inline void copyh(const float *p1, float *p2, const int stride2, const int length)
203 {
204 int i;
205
206 for (i = 0; i < length; i++) {
207 *p2 = p1[i];
208 p2 += stride2;
209 }
210 }
211
212 // Do symmetric extension of data using prescribed symmetries
213 // Original values are in output[npad] through output[npad+size-1]
214 // New values will be placed in output[0] through output[npad] and in output[npad+size] through output[2*npad+size-1] (note: end values may not be filled in)
215 // extension at left bdry is ... 3 2 1 0 | 0 1 2 3 ...
216 // same for right boundary
217 // if right_ext=1 then ... 3 2 1 0 | 1 2 3
218 static void symmetric_extension(float *output, const int size, const int left_ext, const int right_ext)
219 {
220 int first = NPAD;
221 int last = NPAD - 1 + size;
222 const int originalLast = last;
223 int i, nextend, idx;
224
225 if (left_ext == 2)
226 output[--first] = output[NPAD];
227 if (right_ext == 2)
228 output[++last] = output[originalLast];
229
230 // extend left end
231 nextend = first;
232 for (i = 0; i < nextend; i++)
233 output[--first] = output[NPAD + 1 + i];
234
235 idx = NPAD + NPAD - 1 + size;
236
237 // extend right end
238 nextend = idx - last;
239 for (i = 0; i < nextend; i++)
240 output[++last] = output[originalLast - 1 - i];
241 }
242
243 static void transform_step(float *input, float *output, const int size, const int low_size, VagueDenoiserContext *s)
244 {
245 int i;
246
247 symmetric_extension(input, size, 1, 1);
248
249 for (i = NPAD; i < NPAD + low_size; i++) {
250 const float a = input[2 * i - 14] * analysis_low[0];
251 const float b = input[2 * i - 13] * analysis_low[1];
252 const float c = input[2 * i - 12] * analysis_low[2];
253 const float d = input[2 * i - 11] * analysis_low[3];
254 const float e = input[2 * i - 10] * analysis_low[4];
255 const float f = input[2 * i - 9] * analysis_low[3];
256 const float g = input[2 * i - 8] * analysis_low[2];
257 const float h = input[2 * i - 7] * analysis_low[1];
258 const float k = input[2 * i - 6] * analysis_low[0];
259
260 output[i] = a + b + c + d + e + f + g + h + k;
261 }
262
263 for (i = NPAD; i < NPAD + low_size; i++) {
264 const float a = input[2 * i - 12] * analysis_high[0];
265 const float b = input[2 * i - 11] * analysis_high[1];
266 const float c = input[2 * i - 10] * analysis_high[2];
267 const float d = input[2 * i - 9] * analysis_high[3];
268 const float e = input[2 * i - 8] * analysis_high[2];
269 const float f = input[2 * i - 7] * analysis_high[1];
270 const float g = input[2 * i - 6] * analysis_high[0];
271
272 output[i + low_size] = a + b + c + d + e + f + g;
273 }
274 }
275
276 static void invert_step(const float *input, float *output, float *temp, const int size, VagueDenoiserContext *s)
277 {
278 const int low_size = (size + 1) >> 1;
279 const int high_size = size >> 1;
280 int left_ext = 1, right_ext, i;
281 int findex;
282
283 memcpy(temp + NPAD, input + NPAD, low_size * sizeof(float));
284
285 right_ext = (size % 2 == 0) ? 2 : 1;
286 symmetric_extension(temp, low_size, left_ext, right_ext);
287
288 memset(output, 0, (NPAD + NPAD + size) * sizeof(float));
289 findex = (size + 2) >> 1;
290
291 for (i = 9; i < findex + 11; i++) {
292 const float a = temp[i] * synthesis_low[0];
293 const float b = temp[i] * synthesis_low[1];
294 const float c = temp[i] * synthesis_low[2];
295 const float d = temp[i] * synthesis_low[3];
296
297 output[2 * i - 13] += a;
298 output[2 * i - 12] += b;
299 output[2 * i - 11] += c;
300 output[2 * i - 10] += d;
301 output[2 * i - 9] += c;
302 output[2 * i - 8] += b;
303 output[2 * i - 7] += a;
304 }
305
306 memcpy(temp + NPAD, input + NPAD + low_size, high_size * sizeof(float));
307
308 left_ext = 2;
309 right_ext = (size % 2 == 0) ? 1 : 2;
310 symmetric_extension(temp, high_size, left_ext, right_ext);
311
312 for (i = 8; i < findex + 11; i++) {
313 const float a = temp[i] * synthesis_high[0];
314 const float b = temp[i] * synthesis_high[1];
315 const float c = temp[i] * synthesis_high[2];
316 const float d = temp[i] * synthesis_high[3];
317 const float e = temp[i] * synthesis_high[4];
318
319 output[2 * i - 13] += a;
320 output[2 * i - 12] += b;
321 output[2 * i - 11] += c;
322 output[2 * i - 10] += d;
323 output[2 * i - 9] += e;
324 output[2 * i - 8] += d;
325 output[2 * i - 7] += c;
326 output[2 * i - 6] += b;
327 output[2 * i - 5] += a;
328 }
329 }
330
331 static void hard_thresholding(float *block, const int width, const int height,
332 const int stride, const float threshold,
333 const float percent)
334 {
335 const float frac = 1.f - percent * 0.01f;
336 int y, x;
337
338 for (y = 0; y < height; y++) {
339 for (x = 0; x < width; x++) {
340 if (FFABS(block[x]) <= threshold)
341 block[x] *= frac;
342 }
343 block += stride;
344 }
345 }
346
347 static void soft_thresholding(float *block, const int width, const int height, const int stride,
348 const float threshold, const float percent)
349 {
350 const float frac = 1.f - percent * 0.01f;
351 const float shift = threshold * 0.01f * percent;
352 int y, x;
353
354 for (y = 0; y < height; y++) {
355 for (x = 0; x < width; x++) {
356 const float temp = FFABS(block[x]);
357 if (temp <= threshold)
358 block[x] *= frac;
359 else
360 block[x] = (block[x] < 0.f ? -1.f : (block[x] > 0.f ? 1.f : 0.f)) * (temp - shift);
361 }
362 block += stride;
363 }
364 }
365
366 static void qian_thresholding(float *block, const int width, const int height,
367 const int stride, const float threshold,
368 const float percent)
369 {
370 const float percent01 = percent * 0.01f;
371 const float tr2 = threshold * threshold * percent01;
372 const float frac = 1.f - percent01;
373 int y, x;
374
375 for (y = 0; y < height; y++) {
376 for (x = 0; x < width; x++) {
377 const float temp = FFABS(block[x]);
378 if (temp <= threshold) {
379 block[x] *= frac;
380 } else {
381 const float tp2 = temp * temp;
382 block[x] *= (tp2 - tr2) / tp2;
383 }
384 }
385 block += stride;
386 }
387 }
388
389 static float bayes_threshold(float *block, const int width, const int height,
390 const int stride, const float threshold)
391 {
392 float mean = 0.f;
393
394 for (int y = 0; y < height; y++) {
395 for (int x = 0; x < width; x++) {
396 mean += block[x] * block[x];
397 }
398 block += stride;
399 }
400
401 mean /= width * height;
402
403 return threshold * threshold / (FFMAX(sqrtf(mean - threshold), FLT_EPSILON));
404 }
405
406 static void filter(VagueDenoiserContext *s, AVFrame *in, AVFrame *out)
407 {
408 int p, y, x, i, j;
409
410 for (p = 0; p < s->nb_planes; p++) {
411 const int height = s->planeheight[p];
412 const int width = s->planewidth[p];
413 const uint8_t *srcp8 = in->data[p];
414 const uint16_t *srcp16 = (const uint16_t *)in->data[p];
415 uint8_t *dstp8 = out->data[p];
416 uint16_t *dstp16 = (uint16_t *)out->data[p];
417 float *output = s->block;
418 int h_low_size0 = width;
419 int v_low_size0 = height;
420 int nsteps_transform = s->nsteps;
421 int nsteps_invert = s->nsteps;
422 const float *input = s->block;
423
424 if (!((1 << p) & s->planes)) {
425 av_image_copy_plane(out->data[p], out->linesize[p], in->data[p], in->linesize[p],
426 s->planewidth[p] * s->bpc, s->planeheight[p]);
427 continue;
428 }
429
430 if (s->depth <= 8) {
431 for (y = 0; y < height; y++) {
432 for (x = 0; x < width; x++)
433 output[x] = srcp8[x];
434 srcp8 += in->linesize[p];
435 output += width;
436 }
437 } else {
438 for (y = 0; y < height; y++) {
439 for (x = 0; x < width; x++)
440 output[x] = srcp16[x];
441 srcp16 += in->linesize[p] / 2;
442 output += width;
443 }
444 }
445
446 while (nsteps_transform--) {
447 int low_size = (h_low_size0 + 1) >> 1;
448 float *input = s->block;
449 for (j = 0; j < v_low_size0; j++) {
450 copy(input, s->in + NPAD, h_low_size0);
451 transform_step(s->in, s->out, h_low_size0, low_size, s);
452 copy(s->out + NPAD, input, h_low_size0);
453 input += width;
454 }
455
456 low_size = (v_low_size0 + 1) >> 1;
457 input = s->block;
458 for (j = 0; j < h_low_size0; j++) {
459 copyv(input, width, s->in + NPAD, v_low_size0);
460 transform_step(s->in, s->out, v_low_size0, low_size, s);
461 copyh(s->out + NPAD, input, width, v_low_size0);
462 input++;
463 }
464
465 h_low_size0 = (h_low_size0 + 1) >> 1;
466 v_low_size0 = (v_low_size0 + 1) >> 1;
467 }
468
469 if (s->type == 0) {
470 s->thresholding(s->block, width, height, width, s->threshold, s->percent);
471 } else {
472 for (int n = 0; n < s->nsteps; n++) {
473 float threshold;
474 float *block;
475
476 if (n == s->nsteps - 1) {
477 threshold = bayes_threshold(s->block, s->hlowsize[p][n], s->vlowsize[p][n], width, s->threshold);
478 s->thresholding(s->block, s->hlowsize[p][n], s->vlowsize[p][n], width, threshold, s->percent);
479 }
480 block = s->block + s->hlowsize[p][n];
481 threshold = bayes_threshold(block, s->hhighsize[p][n], s->vlowsize[p][n], width, s->threshold);
482 s->thresholding(block, s->hhighsize[p][n], s->vlowsize[p][n], width, threshold, s->percent);
483 block = s->block + s->vlowsize[p][n] * width;
484 threshold = bayes_threshold(block, s->hlowsize[p][n], s->vhighsize[p][n], width, s->threshold);
485 s->thresholding(block, s->hlowsize[p][n], s->vhighsize[p][n], width, threshold, s->percent);
486 block = s->block + s->hlowsize[p][n] + s->vlowsize[p][n] * width;
487 threshold = bayes_threshold(block, s->hhighsize[p][n], s->vhighsize[p][n], width, s->threshold);
488 s->thresholding(block, s->hhighsize[p][n], s->vhighsize[p][n], width, threshold, s->percent);
489 }
490 }
491
492 while (nsteps_invert--) {
493 const int idx = s->vlowsize[p][nsteps_invert] + s->vhighsize[p][nsteps_invert];
494 const int idx2 = s->hlowsize[p][nsteps_invert] + s->hhighsize[p][nsteps_invert];
495 float * idx3 = s->block;
496 for (i = 0; i < idx2; i++) {
497 copyv(idx3, width, s->in + NPAD, idx);
498 invert_step(s->in, s->out, s->tmp, idx, s);
499 copyh(s->out + NPAD, idx3, width, idx);
500 idx3++;
501 }
502
503 idx3 = s->block;
504 for (i = 0; i < idx; i++) {
505 copy(idx3, s->in + NPAD, idx2);
506 invert_step(s->in, s->out, s->tmp, idx2, s);
507 copy(s->out + NPAD, idx3, idx2);
508 idx3 += width;
509 }
510 }
511
512 if (s->depth <= 8) {
513 for (y = 0; y < height; y++) {
514 for (x = 0; x < width; x++)
515 dstp8[x] = av_clip_uint8(input[x] + 0.5f);
516 input += width;
517 dstp8 += out->linesize[p];
518 }
519 } else {
520 for (y = 0; y < height; y++) {
521 for (x = 0; x < width; x++)
522 dstp16[x] = av_clip(input[x] + 0.5f, 0, s->peak);
523 input += width;
524 dstp16 += out->linesize[p] / 2;
525 }
526 }
527 }
528 }
529
530 static int filter_frame(AVFilterLink *inlink, AVFrame *in)
531 {
532 AVFilterContext *ctx = inlink->dst;
533 VagueDenoiserContext *s = ctx->priv;
534 AVFilterLink *outlink = ctx->outputs[0];
535 AVFrame *out;
536 int direct = av_frame_is_writable(in);
537
538 if (direct) {
539 out = in;
540 } else {
541 out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
542 if (!out) {
543 av_frame_free(&in);
544 return AVERROR(ENOMEM);
545 }
546
547 av_frame_copy_props(out, in);
548 }
549
550 filter(s, in, out);
551
552 if (!direct)
553 av_frame_free(&in);
554
555 return ff_filter_frame(outlink, out);
556 }
557
558 static av_cold int init(AVFilterContext *ctx)
559 {
560 VagueDenoiserContext *s = ctx->priv;
561
562 switch (s->method) {
563 case 0:
564 s->thresholding = hard_thresholding;
565 break;
566 case 1:
567 s->thresholding = soft_thresholding;
568 break;
569 case 2:
570 s->thresholding = qian_thresholding;
571 break;
572 }
573
574 return 0;
575 }
576
577 static av_cold void uninit(AVFilterContext *ctx)
578 {
579 VagueDenoiserContext *s = ctx->priv;
580
581 av_freep(&s->block);
582 av_freep(&s->in);
583 av_freep(&s->out);
584 av_freep(&s->tmp);
585 }
586
587 static const AVFilterPad vaguedenoiser_inputs[] = {
588 {
589 .name = "default",
590 .type = AVMEDIA_TYPE_VIDEO,
591 .config_props = config_input,
592 .filter_frame = filter_frame,
593 },
594 };
595
596
597 static const AVFilterPad vaguedenoiser_outputs[] = {
598 {
599 .name = "default",
600 .type = AVMEDIA_TYPE_VIDEO
601 },
602 };
603
604 const AVFilter ff_vf_vaguedenoiser = {
605 .name = "vaguedenoiser",
606 .description = NULL_IF_CONFIG_SMALL("Apply a Wavelet based Denoiser."),
607 .priv_size = sizeof(VagueDenoiserContext),
608 .priv_class = &vaguedenoiser_class,
609 .init = init,
610 .uninit = uninit,
611 FILTER_INPUTS(vaguedenoiser_inputs),
612 FILTER_OUTPUTS(vaguedenoiser_outputs),
613 FILTER_PIXFMTS_ARRAY(pix_fmts),
614 .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC,
615 };
616