golang-image/vp8/reconstruct.go

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// Copyright 2011 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package vp8
// This file implements decoding DCT/WHT residual coefficients and
// reconstructing YCbCr data equal to predicted values plus residuals.
//
// There are 1*16*16 + 2*8*8 + 1*4*4 coefficients per macroblock:
// - 1*16*16 luma DCT coefficients,
// - 2*8*8 chroma DCT coefficients, and
// - 1*4*4 luma WHT coefficients.
// Coefficients are read in lots of 16, and the later coefficients in each lot
// are often zero.
//
// The YCbCr data consists of 1*16*16 luma values and 2*8*8 chroma values,
// plus previously decoded values along the top and left borders. The combined
// values are laid out as a [1+16+1+8][32]uint8 so that vertically adjacent
// samples are 32 bytes apart. In detail, the layout is:
//
// 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1
// . . . . . . . a b b b b b b b b b b b b b b b b c c c c . . . . 0
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 1
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 2
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 3
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y c c c c . . . . 4
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 5
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 6
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 7
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y c c c c . . . . 8
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 9
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 10
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 11
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y c c c c . . . . 12
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 13
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 14
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 15
// . . . . . . . d Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y . . . . . . . . 16
// . . . . . . . e f f f f f f f f . . . . . . . g h h h h h h h h 17
// . . . . . . . i B B B B B B B B . . . . . . . j R R R R R R R R 18
// . . . . . . . i B B B B B B B B . . . . . . . j R R R R R R R R 19
// . . . . . . . i B B B B B B B B . . . . . . . j R R R R R R R R 20
// . . . . . . . i B B B B B B B B . . . . . . . j R R R R R R R R 21
// . . . . . . . i B B B B B B B B . . . . . . . j R R R R R R R R 22
// . . . . . . . i B B B B B B B B . . . . . . . j R R R R R R R R 23
// . . . . . . . i B B B B B B B B . . . . . . . j R R R R R R R R 24
// . . . . . . . i B B B B B B B B . . . . . . . j R R R R R R R R 25
//
// Y, B and R are the reconstructed luma (Y) and chroma (B, R) values.
// The Y values are predicted (either as one 16x16 region or 16 4x4 regions)
// based on the row above's Y values (some combination of {abc} or {dYC}) and
// the column left's Y values (either {ad} or {bY}). Similarly, B and R values
// are predicted on the row above and column left of their respective 8x8
// region: {efi} for B, {ghj} for R.
//
// For uppermost macroblocks (i.e. those with mby == 0), the {abcefgh} values
// are initialized to 0x81. Otherwise, they are copied from the bottom row of
// the macroblock above. The {c} values are then duplicated from row 0 to rows
// 4, 8 and 12 of the ybr workspace.
// Similarly, for leftmost macroblocks (i.e. those with mbx == 0), the {adeigj}
// values are initialized to 0x7f. Otherwise, they are copied from the right
// column of the macroblock to the left.
// For the top-left macroblock (with mby == 0 && mbx == 0), {aeg} is 0x81.
//
// When moving from one macroblock to the next horizontally, the {adeigj}
// values can simply be copied from the workspace to itself, shifted by 8 or
// 16 columns. When moving from one macroblock to the next vertically,
// filtering can occur and hence the row values have to be copied from the
// post-filtered image instead of the pre-filtered workspace.
const (
bCoeffBase = 1*16*16 + 0*8*8
rCoeffBase = 1*16*16 + 1*8*8
whtCoeffBase = 1*16*16 + 2*8*8
)
const (
ybrYX = 8
ybrYY = 1
ybrBX = 8
ybrBY = 18
ybrRX = 24
ybrRY = 18
)
// prepareYBR prepares the {abcdefghij} elements of ybr.
func (d *Decoder) prepareYBR(mbx, mby int) {
if mbx == 0 {
for y := 0; y < 17; y++ {
d.ybr[y][7] = 0x81
}
for y := 17; y < 26; y++ {
d.ybr[y][7] = 0x81
d.ybr[y][23] = 0x81
}
} else {
for y := 0; y < 17; y++ {
d.ybr[y][7] = d.ybr[y][7+16]
}
for y := 17; y < 26; y++ {
d.ybr[y][7] = d.ybr[y][15]
d.ybr[y][23] = d.ybr[y][31]
}
}
if mby == 0 {
for x := 7; x < 28; x++ {
d.ybr[0][x] = 0x7f
}
for x := 7; x < 16; x++ {
d.ybr[17][x] = 0x7f
}
for x := 23; x < 32; x++ {
d.ybr[17][x] = 0x7f
}
} else {
for i := 0; i < 16; i++ {
d.ybr[0][8+i] = d.img.Y[(16*mby-1)*d.img.YStride+16*mbx+i]
}
for i := 0; i < 8; i++ {
d.ybr[17][8+i] = d.img.Cb[(8*mby-1)*d.img.CStride+8*mbx+i]
}
for i := 0; i < 8; i++ {
d.ybr[17][24+i] = d.img.Cr[(8*mby-1)*d.img.CStride+8*mbx+i]
}
if mbx == d.mbw-1 {
for i := 16; i < 20; i++ {
d.ybr[0][8+i] = d.img.Y[(16*mby-1)*d.img.YStride+16*mbx+15]
}
} else {
for i := 16; i < 20; i++ {
d.ybr[0][8+i] = d.img.Y[(16*mby-1)*d.img.YStride+16*mbx+i]
}
}
}
for y := 4; y < 16; y += 4 {
d.ybr[y][24] = d.ybr[0][24]
d.ybr[y][25] = d.ybr[0][25]
d.ybr[y][26] = d.ybr[0][26]
d.ybr[y][27] = d.ybr[0][27]
}
}
// btou converts a bool to a 0/1 value.
func btou(b bool) uint8 {
if b {
return 1
}
return 0
}
// pack packs four 0/1 values into four bits of a uint32.
func pack(x [4]uint8, shift int) uint32 {
u := uint32(x[0])<<0 | uint32(x[1])<<1 | uint32(x[2])<<2 | uint32(x[3])<<3
return u << uint(shift)
}
// unpack unpacks four 0/1 values from a four-bit value.
var unpack = [16][4]uint8{
{0, 0, 0, 0},
{1, 0, 0, 0},
{0, 1, 0, 0},
{1, 1, 0, 0},
{0, 0, 1, 0},
{1, 0, 1, 0},
{0, 1, 1, 0},
{1, 1, 1, 0},
{0, 0, 0, 1},
{1, 0, 0, 1},
{0, 1, 0, 1},
{1, 1, 0, 1},
{0, 0, 1, 1},
{1, 0, 1, 1},
{0, 1, 1, 1},
{1, 1, 1, 1},
}
var (
// The mapping from 4x4 region position to band is specified in section 13.3.
bands = [17]uint8{0, 1, 2, 3, 6, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6, 7, 0}
// Category probabilties are specified in section 13.2.
// Decoding categories 1 and 2 are done inline.
cat3456 = [4][12]uint8{
{173, 148, 140, 0, 0, 0, 0, 0, 0, 0, 0, 0},
{176, 155, 140, 135, 0, 0, 0, 0, 0, 0, 0, 0},
{180, 157, 141, 134, 130, 0, 0, 0, 0, 0, 0, 0},
{254, 254, 243, 230, 196, 177, 153, 140, 133, 130, 129, 0},
}
// The zigzag order is:
// 0 1 5 6
// 2 4 7 12
// 3 8 11 13
// 9 10 14 15
zigzag = [16]uint8{0, 1, 4, 8, 5, 2, 3, 6, 9, 12, 13, 10, 7, 11, 14, 15}
)
// parseResiduals4 parses a 4x4 region of residual coefficients, as specified
// in section 13.3, and returns a 0/1 value indicating whether there was at
// least one non-zero coefficient.
// r is the partition to read bits from.
// plane and context describe which token probability table to use. context is
// either 0, 1 or 2, and equals how many of the macroblock left and macroblock
// above have non-zero coefficients.
// quant are the DC/AC quantization factors.
// skipFirstCoeff is whether the DC coefficient has already been parsed.
// coeffBase is the base index of d.coeff to write to.
func (d *Decoder) parseResiduals4(r *partition, plane int, context uint8, quant [2]uint16, skipFirstCoeff bool, coeffBase int) uint8 {
prob, n := &d.tokenProb[plane], 0
if skipFirstCoeff {
n = 1
}
p := prob[bands[n]][context]
if !r.readBit(p[0]) {
return 0
}
for n != 16 {
n++
if !r.readBit(p[1]) {
p = prob[bands[n]][0]
continue
}
var v uint32
if !r.readBit(p[2]) {
v = 1
p = prob[bands[n]][1]
} else {
if !r.readBit(p[3]) {
if !r.readBit(p[4]) {
v = 2
} else {
v = 3 + r.readUint(p[5], 1)
}
} else if !r.readBit(p[6]) {
if !r.readBit(p[7]) {
// Category 1.
v = 5 + r.readUint(159, 1)
} else {
// Category 2.
v = 7 + 2*r.readUint(165, 1) + r.readUint(145, 1)
}
} else {
// Categories 3, 4, 5 or 6.
b1 := r.readUint(p[8], 1)
b0 := r.readUint(p[9+b1], 1)
cat := 2*b1 + b0
tab := &cat3456[cat]
v = 0
for i := 0; tab[i] != 0; i++ {
v *= 2
v += r.readUint(tab[i], 1)
}
v += 3 + (8 << cat)
}
p = prob[bands[n]][2]
}
z := zigzag[n-1]
c := int32(v) * int32(quant[btou(z > 0)])
if r.readBit(uniformProb) {
c = -c
}
d.coeff[coeffBase+int(z)] = int16(c)
if n == 16 || !r.readBit(p[0]) {
return 1
}
}
return 1
}
vp8: skip filtering for all-zero-DC macroblock residuals. This makes the Go code match the libwebp C code's output on blue-purple-pink-large.*-filter.lossy.webp Also make the various WEBP benchmarks all decode a similar image, the image at http://blog.golang.org/gophercon/image01.jpg, to make it more meaningful to e.g. compare the simple filter's numbers with the normal filter's numbers. Also fix a "go vet" warning in webp/decode.go. The test data was generated by: wget http://blog.golang.org/gophercon/image01.jpg -O blue-purple-pink-large.jpeg convert blue-purple-pink-large.jpeg blue-purple-pink-large.png cwebp -lossless blue-purple-pink-large.png -o blue-purple-pink-large.lossless.webp cwebp -q 80 -f 0 blue-purple-pink-large.png -o blue-purple-pink-large.no-filter.lossy.webp cwebp -q 80 -strong blue-purple-pink-large.png -o blue-purple-pink-large.normal-filter.lossy.webp cwebp -q 80 -nostrong blue-purple-pink-large.png -o blue-purple-pink-large.simple-filter.lossy.webp dwebp -pgm blue-purple-pink-large.no-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.no-filter.lossy.webp.ycbcr.png && rm tmp.pgm dwebp -pgm blue-purple-pink-large.normal-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.normal-filter.lossy.webp.ycbcr.png && rm tmp.pgm dwebp -pgm blue-purple-pink-large.simple-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.simple-filter.lossy.webp.ycbcr.png && rm tmp.pgm LGTM=r R=r CC=golang-codereviews https://golang.org/cl/106230044
2014-06-30 02:36:25 +02:00
// parseResiduals parses the residuals and returns whether inner loop filtering
// should be skipped for this macroblock.
func (d *Decoder) parseResiduals(mbx, mby int) (skip bool) {
partition := &d.op[mby&(d.nOP-1)]
plane := planeY1SansY2
quant := &d.quant[d.segment]
// Parse the DC coefficient of each 4x4 luma region.
if d.usePredY16 {
nz := d.parseResiduals4(partition, planeY2, d.leftMB.nzY16+d.upMB[mbx].nzY16, quant.y2, false, whtCoeffBase)
d.leftMB.nzY16 = nz
d.upMB[mbx].nzY16 = nz
d.inverseWHT16()
plane = planeY1WithY2
}
var (
nzDC, nzAC [4]uint8
nzDCMask, nzACMask uint32
coeffBase int
)
// Parse the luma coefficients.
lnz := unpack[d.leftMB.nzMask&0x0f]
unz := unpack[d.upMB[mbx].nzMask&0x0f]
for y := 0; y < 4; y++ {
nz := lnz[y]
for x := 0; x < 4; x++ {
nz = d.parseResiduals4(partition, plane, nz+unz[x], quant.y1, d.usePredY16, coeffBase)
unz[x] = nz
nzAC[x] = nz
nzDC[x] = btou(d.coeff[coeffBase] != 0)
coeffBase += 16
}
lnz[y] = nz
nzDCMask |= pack(nzDC, y*4)
nzACMask |= pack(nzAC, y*4)
}
lnzMask := pack(lnz, 0)
unzMask := pack(unz, 0)
// Parse the chroma coefficients.
lnz = unpack[d.leftMB.nzMask>>4]
unz = unpack[d.upMB[mbx].nzMask>>4]
for c := 0; c < 4; c += 2 {
for y := 0; y < 2; y++ {
nz := lnz[y+c]
for x := 0; x < 2; x++ {
nz = d.parseResiduals4(partition, planeUV, nz+unz[x+c], quant.uv, false, coeffBase)
unz[x+c] = nz
nzAC[y*2+x] = nz
nzDC[y*2+x] = btou(d.coeff[coeffBase] != 0)
coeffBase += 16
}
lnz[y+c] = nz
}
nzDCMask |= pack(nzDC, 16+c*2)
nzACMask |= pack(nzAC, 16+c*2)
}
lnzMask |= pack(lnz, 4)
unzMask |= pack(unz, 4)
// Save decoder state.
d.leftMB.nzMask = uint8(lnzMask)
d.upMB[mbx].nzMask = uint8(unzMask)
d.nzDCMask = nzDCMask
d.nzACMask = nzACMask
vp8: skip filtering for all-zero-DC macroblock residuals. This makes the Go code match the libwebp C code's output on blue-purple-pink-large.*-filter.lossy.webp Also make the various WEBP benchmarks all decode a similar image, the image at http://blog.golang.org/gophercon/image01.jpg, to make it more meaningful to e.g. compare the simple filter's numbers with the normal filter's numbers. Also fix a "go vet" warning in webp/decode.go. The test data was generated by: wget http://blog.golang.org/gophercon/image01.jpg -O blue-purple-pink-large.jpeg convert blue-purple-pink-large.jpeg blue-purple-pink-large.png cwebp -lossless blue-purple-pink-large.png -o blue-purple-pink-large.lossless.webp cwebp -q 80 -f 0 blue-purple-pink-large.png -o blue-purple-pink-large.no-filter.lossy.webp cwebp -q 80 -strong blue-purple-pink-large.png -o blue-purple-pink-large.normal-filter.lossy.webp cwebp -q 80 -nostrong blue-purple-pink-large.png -o blue-purple-pink-large.simple-filter.lossy.webp dwebp -pgm blue-purple-pink-large.no-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.no-filter.lossy.webp.ycbcr.png && rm tmp.pgm dwebp -pgm blue-purple-pink-large.normal-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.normal-filter.lossy.webp.ycbcr.png && rm tmp.pgm dwebp -pgm blue-purple-pink-large.simple-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.simple-filter.lossy.webp.ycbcr.png && rm tmp.pgm LGTM=r R=r CC=golang-codereviews https://golang.org/cl/106230044
2014-06-30 02:36:25 +02:00
// Section 15.1 of the spec says that "Steps 2 and 4 [of the loop filter]
// are skipped... [if] there is no DCT coefficient coded for the whole
// macroblock."
return nzDCMask == 0 && nzACMask == 0
}
// reconstructMacroblock applies the predictor functions and adds the inverse-
// DCT transformed residuals to recover the YCbCr data.
func (d *Decoder) reconstructMacroblock(mbx, mby int) {
if d.usePredY16 {
p := checkTopLeftPred(mbx, mby, d.predY16)
predFunc16[p](d, 1, 8)
for j := 0; j < 4; j++ {
for i := 0; i < 4; i++ {
n := 4*j + i
y := 4*j + 1
x := 4*i + 8
mask := uint32(1) << uint(n)
if d.nzACMask&mask != 0 {
d.inverseDCT4(y, x, 16*n)
} else if d.nzDCMask&mask != 0 {
d.inverseDCT4DCOnly(y, x, 16*n)
}
}
}
} else {
for j := 0; j < 4; j++ {
for i := 0; i < 4; i++ {
n := 4*j + i
y := 4*j + 1
x := 4*i + 8
predFunc4[d.predY4[j][i]](d, y, x)
mask := uint32(1) << uint(n)
if d.nzACMask&mask != 0 {
d.inverseDCT4(y, x, 16*n)
} else if d.nzDCMask&mask != 0 {
d.inverseDCT4DCOnly(y, x, 16*n)
}
}
}
}
p := checkTopLeftPred(mbx, mby, d.predC8)
predFunc8[p](d, ybrBY, ybrBX)
if d.nzACMask&0x0f0000 != 0 {
d.inverseDCT8(ybrBY, ybrBX, bCoeffBase)
} else if d.nzDCMask&0x0f0000 != 0 {
d.inverseDCT8DCOnly(ybrBY, ybrBX, bCoeffBase)
}
predFunc8[p](d, ybrRY, ybrRX)
if d.nzACMask&0xf00000 != 0 {
d.inverseDCT8(ybrRY, ybrRX, rCoeffBase)
} else if d.nzDCMask&0xf00000 != 0 {
d.inverseDCT8DCOnly(ybrRY, ybrRX, rCoeffBase)
}
}
vp8: skip filtering for all-zero-DC macroblock residuals. This makes the Go code match the libwebp C code's output on blue-purple-pink-large.*-filter.lossy.webp Also make the various WEBP benchmarks all decode a similar image, the image at http://blog.golang.org/gophercon/image01.jpg, to make it more meaningful to e.g. compare the simple filter's numbers with the normal filter's numbers. Also fix a "go vet" warning in webp/decode.go. The test data was generated by: wget http://blog.golang.org/gophercon/image01.jpg -O blue-purple-pink-large.jpeg convert blue-purple-pink-large.jpeg blue-purple-pink-large.png cwebp -lossless blue-purple-pink-large.png -o blue-purple-pink-large.lossless.webp cwebp -q 80 -f 0 blue-purple-pink-large.png -o blue-purple-pink-large.no-filter.lossy.webp cwebp -q 80 -strong blue-purple-pink-large.png -o blue-purple-pink-large.normal-filter.lossy.webp cwebp -q 80 -nostrong blue-purple-pink-large.png -o blue-purple-pink-large.simple-filter.lossy.webp dwebp -pgm blue-purple-pink-large.no-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.no-filter.lossy.webp.ycbcr.png && rm tmp.pgm dwebp -pgm blue-purple-pink-large.normal-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.normal-filter.lossy.webp.ycbcr.png && rm tmp.pgm dwebp -pgm blue-purple-pink-large.simple-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.simple-filter.lossy.webp.ycbcr.png && rm tmp.pgm LGTM=r R=r CC=golang-codereviews https://golang.org/cl/106230044
2014-06-30 02:36:25 +02:00
// reconstruct reconstructs one macroblock and returns whether inner loop
// filtering should be skipped for it.
func (d *Decoder) reconstruct(mbx, mby int) (skip bool) {
if d.segmentHeader.updateMap {
if !d.fp.readBit(d.segmentHeader.prob[0]) {
d.segment = int(d.fp.readUint(d.segmentHeader.prob[1], 1))
} else {
d.segment = int(d.fp.readUint(d.segmentHeader.prob[2], 1)) + 2
}
}
if d.useSkipProb {
skip = d.fp.readBit(d.skipProb)
}
// Prepare the workspace.
for i := range d.coeff {
d.coeff[i] = 0
}
d.prepareYBR(mbx, mby)
// Parse the predictor modes.
d.usePredY16 = d.fp.readBit(145)
if d.usePredY16 {
d.parsePredModeY16(mbx)
} else {
d.parsePredModeY4(mbx)
}
d.parsePredModeC8()
// Parse the residuals.
if !skip {
vp8: skip filtering for all-zero-DC macroblock residuals. This makes the Go code match the libwebp C code's output on blue-purple-pink-large.*-filter.lossy.webp Also make the various WEBP benchmarks all decode a similar image, the image at http://blog.golang.org/gophercon/image01.jpg, to make it more meaningful to e.g. compare the simple filter's numbers with the normal filter's numbers. Also fix a "go vet" warning in webp/decode.go. The test data was generated by: wget http://blog.golang.org/gophercon/image01.jpg -O blue-purple-pink-large.jpeg convert blue-purple-pink-large.jpeg blue-purple-pink-large.png cwebp -lossless blue-purple-pink-large.png -o blue-purple-pink-large.lossless.webp cwebp -q 80 -f 0 blue-purple-pink-large.png -o blue-purple-pink-large.no-filter.lossy.webp cwebp -q 80 -strong blue-purple-pink-large.png -o blue-purple-pink-large.normal-filter.lossy.webp cwebp -q 80 -nostrong blue-purple-pink-large.png -o blue-purple-pink-large.simple-filter.lossy.webp dwebp -pgm blue-purple-pink-large.no-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.no-filter.lossy.webp.ycbcr.png && rm tmp.pgm dwebp -pgm blue-purple-pink-large.normal-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.normal-filter.lossy.webp.ycbcr.png && rm tmp.pgm dwebp -pgm blue-purple-pink-large.simple-filter.lossy.webp -o tmp.pgm && convert tmp.pgm blue-purple-pink-large.simple-filter.lossy.webp.ycbcr.png && rm tmp.pgm LGTM=r R=r CC=golang-codereviews https://golang.org/cl/106230044
2014-06-30 02:36:25 +02:00
skip = d.parseResiduals(mbx, mby)
} else {
if d.usePredY16 {
d.leftMB.nzY16 = 0
d.upMB[mbx].nzY16 = 0
}
d.leftMB.nzMask = 0
d.upMB[mbx].nzMask = 0
d.nzDCMask = 0
d.nzACMask = 0
}
// Reconstruct the YCbCr data and copy it to the image.
d.reconstructMacroblock(mbx, mby)
for i, y := (mby*d.img.YStride+mbx)*16, 0; y < 16; i, y = i+d.img.YStride, y+1 {
copy(d.img.Y[i:i+16], d.ybr[ybrYY+y][ybrYX:ybrYX+16])
}
for i, y := (mby*d.img.CStride+mbx)*8, 0; y < 8; i, y = i+d.img.CStride, y+1 {
copy(d.img.Cb[i:i+8], d.ybr[ybrBY+y][ybrBX:ybrBX+8])
copy(d.img.Cr[i:i+8], d.ybr[ybrRY+y][ybrRX:ybrRX+8])
}
return skip
}