avfilter: add vaguedenoiser filter

1 files changed, 562 insertions, 0 deletions

diff --git a/libavfilter/vf_vaguedenoiser.c b/libavfilter/vf_vaguedenoiser.c
new file mode 100644
index 0000000000..eca1191bbf
--- /dev/null
+++ b/libavfilter/vf_vaguedenoiser.c
@@ -0,0 +1,562 @@
+/*
+ * Copyright (c) 2003 LeFunGus, lefungus@altern.org
+ *
+ * This file is part of FFmpeg
+ *
+ * FFmpeg is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 2 of the License, or
+ * (at your option) any later version.
+ *
+ * FFmpeg is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License along
+ * with FFmpeg; if not, write to the Free Software Foundation, Inc.,
+ * 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ */
+
+#include <float.h>
+
+#include "libavutil/imgutils.h"
+#include "libavutil/attributes.h"
+#include "libavutil/common.h"
+#include "libavutil/pixdesc.h"
+#include "libavutil/intreadwrite.h"
+#include "libavutil/opt.h"
+
+#include "avfilter.h"
+#include "formats.h"
+#include "internal.h"
+#include "video.h"
+
+typedef struct VagueDenoiserContext {
+    const AVClass *class;
+
+    float threshold;
+    float percent;
+    int method;
+    int nsteps;
+    int planes;
+
+    int depth;
+    int peak;
+    int nb_planes;
+    int planeheight[4];
+    int planewidth[4];
+
+    float *block;
+    float *in;
+    float *out;
+    float *tmp;
+
+    int hlowsize[32];
+    int hhighsize[32];
+    int vlowsize[32];
+    int vhighsize[32];
+} VagueDenoiserContext;
+
+#define OFFSET(x) offsetof(VagueDenoiserContext, x)
+#define FLAGS AV_OPT_FLAG_VIDEO_PARAM | AV_OPT_FLAG_FILTERING_PARAM
+static const AVOption vaguedenoiser_options[] = {
+    { "threshold", "set filtering strength",   OFFSET(threshold), AV_OPT_TYPE_FLOAT, {.dbl=2.},  0,DBL_MAX, FLAGS },
+    { "method",    "set filtering method",     OFFSET(method),    AV_OPT_TYPE_INT,   {.i64=2 },  0, 2,      FLAGS, "method" },
+        { "hard",   "hard thresholding",       0,                 AV_OPT_TYPE_CONST, {.i64=0},   0, 0,      FLAGS, "method" },
+        { "soft",   "soft thresholding",       0,                 AV_OPT_TYPE_CONST, {.i64=1},   0, 0,      FLAGS, "method" },
+        { "garrote", "garotte thresholding",   0,                 AV_OPT_TYPE_CONST, {.i64=2},   0, 0,      FLAGS, "method" },
+    { "nsteps",    "set number of steps",      OFFSET(nsteps),    AV_OPT_TYPE_INT,   {.i64=6 },  1, 32,     FLAGS },
+    { "percent", "set percent of full denoising", OFFSET(percent),AV_OPT_TYPE_FLOAT, {.dbl=85},  0,100,     FLAGS },
+    { "planes",    "set planes to filter",     OFFSET(planes),    AV_OPT_TYPE_INT,   {.i64=15 }, 0, 15,     FLAGS },
+    { NULL }
+};
+
+AVFILTER_DEFINE_CLASS(vaguedenoiser);
+
+#define NPAD 10
+
+static const float analysis_low[9] = {
+    0.037828455506995f, -0.023849465019380f, -0.110624404418423f, 0.377402855612654f,
+    0.852698679009403f, 0.377402855612654f, -0.110624404418423f, -0.023849465019380f, 0.037828455506995f
+};
+
+static const float analysis_high[7] = {
+    -0.064538882628938f, 0.040689417609558f, 0.418092273222212f, -0.788485616405664f,
+    0.418092273222212f, 0.040689417609558f, -0.064538882628938f
+};
+
+static const float synthesis_low[7] = {
+    -0.064538882628938f, -0.040689417609558f, 0.418092273222212f, 0.788485616405664f,
+    0.418092273222212f, -0.040689417609558f, -0.064538882628938f
+};
+
+static const float synthesis_high[9] = {
+    -0.037828455506995f, -0.023849465019380f, 0.110624404418423f, 0.377402855612654f,
+    -0.852698679009403f, 0.377402855612654f, 0.110624404418423f, -0.023849465019380f, -0.037828455506995f
+};
+
+static int query_formats(AVFilterContext *ctx)
+{
+    static const enum AVPixelFormat pix_fmts[] = {
+        AV_PIX_FMT_GRAY8,
+        AV_PIX_FMT_GRAY16,
+        AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P,
+        AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P,
+        AV_PIX_FMT_YUV440P, AV_PIX_FMT_YUV444P,
+        AV_PIX_FMT_YUVJ420P, AV_PIX_FMT_YUVJ422P,
+        AV_PIX_FMT_YUVJ440P, AV_PIX_FMT_YUVJ444P,
+        AV_PIX_FMT_YUVJ411P,
+        AV_PIX_FMT_YUV420P9, AV_PIX_FMT_YUV422P9, AV_PIX_FMT_YUV444P9,
+        AV_PIX_FMT_YUV420P10, AV_PIX_FMT_YUV422P10, AV_PIX_FMT_YUV444P10,
+        AV_PIX_FMT_YUV440P10,
+        AV_PIX_FMT_YUV444P12, AV_PIX_FMT_YUV422P12, AV_PIX_FMT_YUV420P12,
+        AV_PIX_FMT_YUV440P12,
+        AV_PIX_FMT_YUV444P14, AV_PIX_FMT_YUV422P14, AV_PIX_FMT_YUV420P14,
+        AV_PIX_FMT_YUV420P16, AV_PIX_FMT_YUV422P16, AV_PIX_FMT_YUV444P16,
+        AV_PIX_FMT_GBRP, AV_PIX_FMT_GBRP9, AV_PIX_FMT_GBRP10,
+        AV_PIX_FMT_GBRP12, AV_PIX_FMT_GBRP14, AV_PIX_FMT_GBRP16,
+        AV_PIX_FMT_NONE
+    };
+    AVFilterFormats *fmts_list = ff_make_format_list(pix_fmts);
+    if (!fmts_list)
+        return AVERROR(ENOMEM);
+    return ff_set_common_formats(ctx, fmts_list);
+}
+
+static int config_input(AVFilterLink *inlink)
+{
+    VagueDenoiserContext *s = inlink->dst->priv;
+    const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format);
+    int nsteps_width, nsteps_height, nsteps_max;
+
+    s->depth = desc->comp[0].depth;
+    s->nb_planes = desc->nb_components;
+
+    s->planeheight[1] = s->planeheight[2] = AV_CEIL_RSHIFT(inlink->h, desc->log2_chroma_h);
+    s->planeheight[0] = s->planeheight[3] = inlink->h;
+    s->planewidth[1]  = s->planewidth[2]  = AV_CEIL_RSHIFT(inlink->w, desc->log2_chroma_w);
+    s->planewidth[0]  = s->planewidth[3]  = inlink->w;
+
+    s->block = av_malloc_array(inlink->w * inlink->h, sizeof(*s->block));
+    s->in    = av_malloc_array(32 + FFMAX(inlink->w, inlink->h), sizeof(*s->in));
+    s->out   = av_malloc_array(32 + FFMAX(inlink->w, inlink->h), sizeof(*s->out));
+    s->tmp   = av_malloc_array(32 + FFMAX(inlink->w, inlink->h), sizeof(*s->tmp));
+
+    if (!s->block || !s->in || !s->out || !s->tmp)
+        return AVERROR(ENOMEM);
+
+    s->threshold *= 1 << (s->depth - 8);
+    s->peak = (1 << s->depth) - 1;
+
+    nsteps_width  = ((s->planes & 2 || s->planes & 4) && s->nb_planes > 1) ? s->planewidth[1] : s->planewidth[0];
+    nsteps_height = ((s->planes & 2 || s->planes & 4) && s->nb_planes > 1) ? s->planeheight[1] : s->planeheight[0];
+
+    for (nsteps_max = 1; nsteps_max < 15; nsteps_max++) {
+        if (pow(2, nsteps_max) >= nsteps_width || pow(2, nsteps_max) >= nsteps_height)
+            break;
+    }
+
+    s->nsteps = FFMIN(s->nsteps, nsteps_max - 2);
+
+    return 0;
+}
+
+static inline void copy(const float *p1, float *p2, const int length)
+{
+    memcpy(p2, p1, length * sizeof(float));
+}
+
+static inline void copyv(const float *p1, const int stride1, float *p2, const int length)
+{
+    int i;
+
+    for (i = 0; i < length; i++) {
+        p2[i] = *p1;
+        p1 += stride1;
+    }
+}
+
+static inline void copyh(const float *p1, float *p2, const int stride2, const int length)
+{
+    int i;
+
+    for (i = 0; i < length; i++) {
+        *p2 = p1[i];
+        p2 += stride2;
+    }
+}
+
+// Do symmetric extension of data using prescribed symmetries
+// Original values are in output[npad] through output[npad+size-1]
+// 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)
+// extension at left bdry is ... 3 2 1 0 | 0 1 2 3 ...
+// same for right boundary
+// if right_ext=1 then ... 3 2 1 0 | 1 2 3
+static void symmetric_extension(float *output, const int size, const int left_ext, const int right_ext)
+{
+    int first = NPAD;
+    int last = NPAD - 1 + size;
+    const int originalLast = last;
+    int i, nextend, idx;
+
+    if (left_ext == 2)
+        output[--first] = output[NPAD];
+    if (right_ext == 2)
+        output[++last] = output[originalLast];
+
+    // extend left end
+    nextend = first;
+    for (i = 0; i < nextend; i++)
+        output[--first] = output[NPAD + 1 + i];
+
+    idx = NPAD + NPAD - 1 + size;
+
+    // extend right end
+    nextend = idx - last;
+    for (i = 0; i < nextend; i++)
+        output[++last] = output[originalLast - 1 - i];
+}
+
+static void transform_step(float *input, float *output, const int size, const int low_size, VagueDenoiserContext *s)
+{
+    int i;
+
+    symmetric_extension(input, size, 1, 1);
+
+    for (i = NPAD; i < NPAD + low_size; i++) {
+        const float a = input[2 * i - 14] * analysis_low[0];
+        const float b = input[2 * i - 13] * analysis_low[1];
+        const float c = input[2 * i - 12] * analysis_low[2];
+        const float d = input[2 * i - 11] * analysis_low[3];
+        const float e = input[2 * i - 10] * analysis_low[4];
+        const float f = input[2 * i -  9] * analysis_low[3];
+        const float g = input[2 * i -  8] * analysis_low[2];
+        const float h = input[2 * i -  7] * analysis_low[1];
+        const float k = input[2 * i -  6] * analysis_low[0];
+
+        output[i] = a + b + c + d + e + f + g + h + k;
+    }
+
+    for (i = NPAD; i < NPAD + low_size; i++) {
+        const float a = input[2 * i - 12] * analysis_high[0];
+        const float b = input[2 * i - 11] * analysis_high[1];
+        const float c = input[2 * i - 10] * analysis_high[2];
+        const float d = input[2 * i -  9] * analysis_high[3];
+        const float e = input[2 * i -  8] * analysis_high[2];
+        const float f = input[2 * i -  7] * analysis_high[1];
+        const float g = input[2 * i -  6] * analysis_high[0];
+
+        output[i + low_size] = a + b + c + d + e + f + g;
+    }
+}
+
+static void invert_step(const float *input, float *output, float *temp, const int size, VagueDenoiserContext *s)
+{
+    const int low_size = (size + 1) >> 1;
+    const int high_size = size >> 1;
+    int left_ext = 1, right_ext, i;
+    int findex;
+
+    memcpy(temp + NPAD, input + NPAD, low_size * sizeof(float));
+
+    right_ext = (size % 2 == 0) ? 2 : 1;
+    symmetric_extension(temp, low_size, left_ext, right_ext);
+
+    memset(output, 0, (NPAD + NPAD + size) * sizeof(float));
+    findex = (size + 2) >> 1;
+
+    for (i = 9; i < findex + 11; i++) {
+        const float a = temp[i] * synthesis_low[0];
+        const float b = temp[i] * synthesis_low[1];
+        const float c = temp[i] * synthesis_low[2];
+        const float d = temp[i] * synthesis_low[3];
+
+        output[2 * i - 13] += a;
+        output[2 * i - 12] += b;
+        output[2 * i - 11] += c;
+        output[2 * i - 10] += d;
+        output[2 * i -  9] += c;
+        output[2 * i -  8] += b;
+        output[2 * i -  7] += a;
+    }
+
+    memcpy(temp + NPAD, input + NPAD + low_size, high_size * sizeof(float));
+
+    left_ext = 2;
+    right_ext = (size % 2 == 0) ? 1 : 2;
+    symmetric_extension(temp, high_size, left_ext, right_ext);
+
+    for (i = 8; i < findex + 11; i++) {
+        const float a = temp[i] * synthesis_high[0];
+        const float b = temp[i] * synthesis_high[1];
+        const float c = temp[i] * synthesis_high[2];
+        const float d = temp[i] * synthesis_high[3];
+        const float e = temp[i] * synthesis_high[4];
+
+        output[2 * i - 13] += a;
+        output[2 * i - 12] += b;
+        output[2 * i - 11] += c;
+        output[2 * i - 10] += d;
+        output[2 * i -  9] += e;
+        output[2 * i -  8] += d;
+        output[2 * i -  7] += c;
+        output[2 * i -  6] += b;
+        output[2 * i -  5] += a;
+    }
+}
+
+static void hard_thresholding(float *block, const int width, const int height,
+                              const int stride, const float threshold,
+                              const float percent)
+{
+    const float frac = 1.f - percent * 0.01f;
+    int y, x;
+
+    for (y = 0; y < height; y++) {
+        for (x = 0; x < width; x++) {
+            if (FFABS(block[x]) <= threshold)
+                block[x] *= frac;
+        }
+        block += stride;
+    }
+}
+
+static void soft_thresholding(float *block, const int width, const int height, const int stride,
+                              const float threshold, const float percent, const int nsteps)
+{
+    const float frac = 1.f - percent * 0.01f;
+    const float shift = threshold * 0.01f * percent;
+    int w = width;
+    int h = height;
+    int y, x, l;
+
+    for (l = 0; l < nsteps; l++) {
+        w = (w + 1) >> 1;
+        h = (h + 1) >> 1;
+    }
+
+    for (y = 0; y < height; y++) {
+        const int x0 = (y < h) ? w : 0;
+        for (x = x0; x < width; x++) {
+            const float temp = FFABS(block[x]);
+            if (temp <= threshold)
+                block[x] *= frac;
+            else
+                block[x] = (block[x] < 0.f ? -1.f : (block[x] > 0.f ? 1.f : 0.f)) * (temp - shift);
+        }
+        block += stride;
+    }
+}
+
+static void qian_thresholding(float *block, const int width, const int height,
+                              const int stride, const float threshold,
+                              const float percent)
+{
+    const float percent01 = percent * 0.01f;
+    const float tr2 = threshold * threshold * percent01;
+    const float frac = 1.f - percent01;
+    int y, x;
+
+    for (y = 0; y < height; y++) {
+        for (x = 0; x < width; x++) {
+            const float temp = FFABS(block[x]);
+            if (temp <= threshold) {
+                block[x] *= frac;
+            } else {
+                const float tp2 = temp * temp;
+                block[x] *= (tp2 - tr2) / tp2;
+            }
+        }
+        block += stride;
+    }
+}
+
+static void filter(VagueDenoiserContext *s, AVFrame *in, AVFrame *out)
+{
+    int p, y, x, i, j;
+
+    for (p = 0; p < s->nb_planes; p++) {
+        const int height = s->planeheight[p];
+        const int width = s->planewidth[p];
+        const uint8_t *srcp8 = in->data[p];
+        const uint16_t *srcp16 = (const uint16_t *)in->data[p];
+        uint8_t *dstp8 = out->data[p];
+        uint16_t *dstp16 = (uint16_t *)out->data[p];
+        float *output = s->block;
+        int h_low_size0 = width;
+        int v_low_size0 = height;
+        int nsteps_transform = s->nsteps;
+        int nsteps_invert = s->nsteps;
+        const float *input = s->block;
+
+        if (!((1 << p) & s->planes)) {
+            av_image_copy_plane(out->data[p], out->linesize[p], in->data[p], in->linesize[p],
+                                s->planewidth[p], s->planeheight[p]);
+            continue;
+        }
+
+        if (s->depth <= 8) {
+            for (y = 0; y < height; y++) {
+                for (x = 0; x < width; x++)
+                    output[x] = srcp8[x];
+                srcp8 += in->linesize[p];
+                output += width;
+            }
+        } else {
+            for (y = 0; y < height; y++) {
+                for (x = 0; x < width; x++)
+                    output[x] = srcp16[x];
+                srcp16 += in->linesize[p] / 2;
+                output += width;
+            }
+        }
+
+        while (nsteps_transform--) {
+            int low_size = (h_low_size0 + 1) >> 1;
+            float *input = s->block;
+            for (j = 0; j < v_low_size0; j++) {
+                copy(input, s->in + NPAD, h_low_size0);
+                transform_step(s->in, s->out, h_low_size0, low_size, s);
+                copy(s->out + NPAD, input, h_low_size0);
+                input += width;
+            }
+
+            low_size = (v_low_size0 + 1) >> 1;
+            input = s->block;
+            for (j = 0; j < h_low_size0; j++) {
+                copyv(input, width, s->in + NPAD, v_low_size0);
+                transform_step(s->in, s->out, v_low_size0, low_size, s);
+                copyh(s->out + NPAD, input, width, v_low_size0);
+                input++;
+            }
+
+            h_low_size0 = (h_low_size0 + 1) >> 1;
+            v_low_size0 = (v_low_size0 + 1) >> 1;
+        }
+
+        if (s->method == 0)
+            hard_thresholding(s->block, width, height, width, s->threshold, s->percent);
+        else if (s->method == 1)
+            soft_thresholding(s->block, width, height, width, s->threshold, s->percent, s->nsteps);
+        else
+            qian_thresholding(s->block, width, height, width, s->threshold, s->percent);
+
+        s->hlowsize[0]  = (width + 1) >> 1;
+        s->hhighsize[0] = width >> 1;
+        s->vlowsize[0]  = (height + 1) >> 1;
+        s->vhighsize[0] = height >> 1;
+
+        for (i = 1; i < s->nsteps; i++) {
+            s->hlowsize[i]  = (s->hlowsize[i - 1] + 1) >> 1;
+            s->hhighsize[i] = s->hlowsize[i - 1] >> 1;
+            s->vlowsize[i]  = (s->vlowsize[i - 1] + 1) >> 1;
+            s->vhighsize[i] = s->vlowsize[i - 1] >> 1;
+        }
+
+        while (nsteps_invert--) {
+            const int idx = s->vlowsize[nsteps_invert] + s->vhighsize[nsteps_invert];
+            const int idx2 = s->hlowsize[nsteps_invert] + s->hhighsize[nsteps_invert];
+            float * idx3 = s->block;
+            for (i = 0; i < idx2; i++) {
+                copyv(idx3, width, s->in + NPAD, idx);
+                invert_step(s->in, s->out, s->tmp, idx, s);
+                copyh(s->out + NPAD, idx3, width, idx);
+                idx3++;
+            }
+
+            idx3 = s->block;
+            for (i = 0; i < idx; i++) {
+                copy(idx3, s->in + NPAD, idx2);
+                invert_step(s->in, s->out, s->tmp, idx2, s);
+                copy(s->out + NPAD, idx3, idx2);
+                idx3 += width;
+            }
+        }
+
+        if (s->depth <= 8) {
+            for (y = 0; y < height; y++) {
+                for (x = 0; x < width; x++)
+                    dstp8[x] = av_clip_uint8(input[x] + 0.5f);
+                input += width;
+                dstp8 += out->linesize[p];
+            }
+        } else {
+            for (y = 0; y < height; y++) {
+                for (x = 0; x < width; x++)
+                    dstp16[x] = av_clip(input[x] + 0.5f, 0, s->peak);
+                input += width;
+                dstp16 += out->linesize[p] / 2;
+            }
+        }
+    }
+}
+
+static int filter_frame(AVFilterLink *inlink, AVFrame *in)
+{
+    AVFilterContext *ctx  = inlink->dst;
+    VagueDenoiserContext *s = ctx->priv;
+    AVFilterLink *outlink = ctx->outputs[0];
+    AVFrame *out;
+    int direct = av_frame_is_writable(in);
+
+    if (direct) {
+        out = in;
+    } else {
+        out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
+        if (!out) {
+            av_frame_free(&in);
+            return AVERROR(ENOMEM);
+        }
+
+        av_frame_copy_props(out, in);
+    }
+
+    filter(s, in, out);
+
+    if (!direct)
+        av_frame_free(&in);
+
+    return ff_filter_frame(outlink, out);
+}
+
+static av_cold void uninit(AVFilterContext *ctx)
+{
+    VagueDenoiserContext *s = ctx->priv;
+
+    av_freep(&s->block);
+    av_freep(&s->in);
+    av_freep(&s->out);
+    av_freep(&s->tmp);
+}
+
+static const AVFilterPad vaguedenoiser_inputs[] = {
+    {
+        .name         = "default",
+        .type         = AVMEDIA_TYPE_VIDEO,
+        .config_props = config_input,
+        .filter_frame = filter_frame,
+    },
+    { NULL }
+};
+
+
+static const AVFilterPad vaguedenoiser_outputs[] = {
+    {
+        .name = "default",
+        .type = AVMEDIA_TYPE_VIDEO
+    },
+    { NULL }
+};
+
+AVFilter ff_vf_vaguedenoiser = {
+    .name          = "vaguedenoiser",
+    .description   = NULL_IF_CONFIG_SMALL("Apply a Wavelet based Denoiser."),
+    .priv_size     = sizeof(VagueDenoiserContext),
+    .priv_class    = &vaguedenoiser_class,
+    .uninit        = uninit,
+    .query_formats = query_formats,
+    .inputs        = vaguedenoiser_inputs,
+    .outputs       = vaguedenoiser_outputs,
+    .flags         = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC,
+};