dany/libwebp
1
0
Fork 0
mirror of https://github.com/webmproject/libwebp.git synced 2024-12-25 21:28:22 +01:00
Code Issues Actions Packages Projects Releases Wiki Activity

Convert VP8LFastSLog2 to fixed point

Browse Source 
Speedups: 1% with '-lossless', 2% with '-lossless -q 100 -m6'

Change-Id: I1d79ea8e3e9e4bac7bcea4d7cbcc1bd56273988e
This commit is contained in:
Vincent Rabaud 2024-07-09 15:44:18 +02:00
parent 66408c2c7c
commit fb444b692b
7 changed files with 128 additions and 260 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
src/dsp/lossless.h
View File

@ -185,8 +185,8 @@ extern VP8LPredictorAddSubFunc VP8LPredictorsSub_C[16];
typedef uint32_t (*VP8LCostFunc)(const uint32_t* population, int length);
typedef uint32_t (*VP8LCostCombinedFunc)(const uint32_t* X, const uint32_t* Y,
int length);
typedef float (*VP8LCombinedShannonEntropyFunc)(const uint32_t X[256],
const uint32_t Y[256]);
typedef uint64_t (*VP8LCombinedShannonEntropyFunc)(const uint32_t X[256],
const uint32_t Y[256]);
extern VP8LCostFunc VP8LExtraCost;
extern VP8LCostCombinedFunc VP8LExtraCostCombined;
@ -198,7 +198,7 @@ typedef struct { // small struct to hold counters
} VP8LStreaks;
typedef struct { // small struct to hold bit entropy results
float entropy; // entropy
uint64_t entropy; // entropy
uint32_t sum; // sum of the population
int nonzeros; // number of non-zero elements in the population
uint32_t max_val; // maximum value in the population

11
src/dsp/lossless_common.h
View File

@ -82,15 +82,12 @@ static WEBP_INLINE int VP8LNearLosslessBits(int near_lossless_quality) {
#define LOG_2_RECIPROCAL 1.44269504088896338700465094007086
// LOG_2_RECIPROCAL * (1 << LOG_2_PRECISION_BITS)
#define LOG_2_RECIPROCAL_FIXED_DOUBLE 12102203.161561485379934310913085937500
#define LOG_2_RECIPROCAL_FIXED 12102203
#define LOG_2_RECIPROCAL_FIXED ((uint64_t)12102203)
#define LOG_LOOKUP_IDX_MAX 256
extern const uint32_t kLog2Table[LOG_LOOKUP_IDX_MAX];
extern const float kSLog2Table[LOG_LOOKUP_IDX_MAX];
// TODO(vrabaud) remove this table once VP8LFastSLog2 is switched to fixed
// point.
extern const float kLog2fTable[LOG_LOOKUP_IDX_MAX];
extern const uint64_t kSLog2Table[LOG_LOOKUP_IDX_MAX];
typedef uint32_t (*VP8LFastLog2SlowFunc)(uint32_t v);
typedef float (*VP8LFastSLog2SlowFunc)(uint32_t v);
typedef uint64_t (*VP8LFastSLog2SlowFunc)(uint32_t v);
extern VP8LFastLog2SlowFunc VP8LFastLog2Slow;
extern VP8LFastSLog2SlowFunc VP8LFastSLog2Slow;
@ -99,7 +96,7 @@ static WEBP_INLINE uint32_t VP8LFastLog2(uint32_t v) {
return (v < LOG_LOOKUP_IDX_MAX) ? kLog2Table[v] : VP8LFastLog2Slow(v);
}
// Fast calculation of v * log2(v) for integer input.
static WEBP_INLINE float VP8LFastSLog2(uint32_t v) {
static WEBP_INLINE uint64_t VP8LFastSLog2(uint32_t v) {
return (v < LOG_LOOKUP_IDX_MAX) ? kSLog2Table[v] : VP8LFastSLog2Slow(v);
}

320
src/dsp/lossless_enc.c
View File

@ -24,138 +24,6 @@
#include "src/dsp/lossless_common.h"
#include "src/dsp/yuv.h"
// lookup table for small values of log2(int)
const float kLog2fTable[LOG_LOOKUP_IDX_MAX] = {
0.0000000000000000f, 0.0000000000000000f,
1.0000000000000000f, 1.5849625007211560f,
2.0000000000000000f, 2.3219280948873621f,
2.5849625007211560f, 2.8073549220576041f,
3.0000000000000000f, 3.1699250014423121f,
3.3219280948873621f, 3.4594316186372973f,
3.5849625007211560f, 3.7004397181410921f,
3.8073549220576041f, 3.9068905956085187f,
4.0000000000000000f, 4.0874628412503390f,
4.1699250014423121f, 4.2479275134435852f,
4.3219280948873626f, 4.3923174227787606f,
4.4594316186372973f, 4.5235619560570130f,
4.5849625007211560f, 4.6438561897747243f,
4.7004397181410917f, 4.7548875021634682f,
4.8073549220576037f, 4.8579809951275718f,
4.9068905956085187f, 4.9541963103868749f,
5.0000000000000000f, 5.0443941193584533f,
5.0874628412503390f, 5.1292830169449663f,
5.1699250014423121f, 5.2094533656289501f,
5.2479275134435852f, 5.2854022188622487f,
5.3219280948873626f, 5.3575520046180837f,
5.3923174227787606f, 5.4262647547020979f,
5.4594316186372973f, 5.4918530963296747f,
5.5235619560570130f, 5.5545888516776376f,
5.5849625007211560f, 5.6147098441152083f,
5.6438561897747243f, 5.6724253419714951f,
5.7004397181410917f, 5.7279204545631987f,
5.7548875021634682f, 5.7813597135246599f,
5.8073549220576037f, 5.8328900141647412f,
5.8579809951275718f, 5.8826430493618415f,
5.9068905956085187f, 5.9307373375628866f,
5.9541963103868749f, 5.9772799234999167f,
6.0000000000000000f, 6.0223678130284543f,
6.0443941193584533f, 6.0660891904577720f,
6.0874628412503390f, 6.1085244567781691f,
6.1292830169449663f, 6.1497471195046822f,
6.1699250014423121f, 6.1898245588800175f,
6.2094533656289501f, 6.2288186904958804f,
6.2479275134435852f, 6.2667865406949010f,
6.2854022188622487f, 6.3037807481771030f,
6.3219280948873626f, 6.3398500028846243f,
6.3575520046180837f, 6.3750394313469245f,
6.3923174227787606f, 6.4093909361377017f,
6.4262647547020979f, 6.4429434958487279f,
6.4594316186372973f, 6.4757334309663976f,
6.4918530963296747f, 6.5077946401986963f,
6.5235619560570130f, 6.5391588111080309f,
6.5545888516776376f, 6.5698556083309478f,
6.5849625007211560f, 6.5999128421871278f,
6.6147098441152083f, 6.6293566200796094f,
6.6438561897747243f, 6.6582114827517946f,
6.6724253419714951f, 6.6865005271832185f,
6.7004397181410917f, 6.7142455176661224f,
6.7279204545631987f, 6.7414669864011464f,
6.7548875021634682f, 6.7681843247769259f,
6.7813597135246599f, 6.7944158663501061f,
6.8073549220576037f, 6.8201789624151878f,
6.8328900141647412f, 6.8454900509443747f,
6.8579809951275718f, 6.8703647195834047f,
6.8826430493618415f, 6.8948177633079437f,
6.9068905956085187f, 6.9188632372745946f,
6.9307373375628866f, 6.9425145053392398f,
6.9541963103868749f, 6.9657842846620869f,
6.9772799234999167f, 6.9886846867721654f,
7.0000000000000000f, 7.0112272554232539f,
7.0223678130284543f, 7.0334230015374501f,
7.0443941193584533f, 7.0552824355011898f,
7.0660891904577720f, 7.0768155970508308f,
7.0874628412503390f, 7.0980320829605263f,
7.1085244567781691f, 7.1189410727235076f,
7.1292830169449663f, 7.1395513523987936f,
7.1497471195046822f, 7.1598713367783890f,
7.1699250014423121f, 7.1799090900149344f,
7.1898245588800175f, 7.1996723448363644f,
7.2094533656289501f, 7.2191685204621611f,
7.2288186904958804f, 7.2384047393250785f,
7.2479275134435852f, 7.2573878426926521f,
7.2667865406949010f, 7.2761244052742375f,
7.2854022188622487f, 7.2946207488916270f,
7.3037807481771030f, 7.3128829552843557f,
7.3219280948873626f, 7.3309168781146167f,
7.3398500028846243f, 7.3487281542310771f,
7.3575520046180837f, 7.3663222142458160f,
7.3750394313469245f, 7.3837042924740519f,
7.3923174227787606f, 7.4008794362821843f,
7.4093909361377017f, 7.4178525148858982f,
7.4262647547020979f, 7.4346282276367245f,
7.4429434958487279f, 7.4512111118323289f,
7.4594316186372973f, 7.4676055500829976f,
7.4757334309663976f, 7.4838157772642563f,
7.4918530963296747f, 7.4998458870832056f,
7.5077946401986963f, 7.5156998382840427f,
7.5235619560570130f, 7.5313814605163118f,
7.5391588111080309f, 7.5468944598876364f,
7.5545888516776376f, 7.5622424242210728f,
7.5698556083309478f, 7.5774288280357486f,
7.5849625007211560f, 7.5924570372680806f,
7.5999128421871278f, 7.6073303137496104f,
7.6147098441152083f, 7.6220518194563764f,
7.6293566200796094f, 7.6366246205436487f,
7.6438561897747243f, 7.6510516911789281f,
7.6582114827517946f, 7.6653359171851764f,
7.6724253419714951f, 7.6794800995054464f,
7.6865005271832185f, 7.6934869574993252f,
7.7004397181410917f, 7.7073591320808825f,
7.7142455176661224f, 7.7210991887071855f,
7.7279204545631987f, 7.7347096202258383f,
7.7414669864011464f, 7.7481928495894605f,
7.7548875021634682f, 7.7615512324444795f,
7.7681843247769259f, 7.7747870596011736f,
7.7813597135246599f, 7.7879025593914317f,
7.7944158663501061f, 7.8008998999203047f,
7.8073549220576037f, 7.8137811912170374f,
7.8201789624151878f, 7.8265484872909150f,
7.8328900141647412f, 7.8392037880969436f,
7.8454900509443747f, 7.8517490414160571f,
7.8579809951275718f, 7.8641861446542797f,
7.8703647195834047f, 7.8765169465649993f,
7.8826430493618415f, 7.8887432488982591f,
7.8948177633079437f, 7.9008668079807486f,
7.9068905956085187f, 7.9128893362299619f,
7.9188632372745946f, 7.9248125036057812f,
7.9307373375628866f, 7.9366379390025709f,
7.9425145053392398f, 7.9483672315846778f,
7.9541963103868749f, 7.9600019320680805f,
7.9657842846620869f, 7.9715435539507719f,
7.9772799234999167f, 7.9829935746943103f,
7.9886846867721654f, 7.9943534368588577f
};
// lookup table for small values of log2(int) * (1 << LOG_2_PRECISION_BITS).
// Obtained in Python with:
// a = [ str(round((1<<23)*math.log2(i))) if i else "0" for i in range(256)]
@ -201,71 +69,78 @@ const uint32_t kLog2Table[LOG_LOOKUP_IDX_MAX] = {
66918274, 66966204, 67013944, 67061497
};
const float kSLog2Table[LOG_LOOKUP_IDX_MAX] = {
0.00000000f, 0.00000000f, 2.00000000f, 4.75488750f,
8.00000000f, 11.60964047f, 15.50977500f, 19.65148445f,
24.00000000f, 28.52932501f, 33.21928095f, 38.05374781f,
43.01955001f, 48.10571634f, 53.30296891f, 58.60335893f,
64.00000000f, 69.48686830f, 75.05865003f, 80.71062276f,
86.43856190f, 92.23866588f, 98.10749561f, 104.04192499f,
110.03910002f, 116.09640474f, 122.21143267f, 128.38196256f,
134.60593782f, 140.88144886f, 147.20671787f, 153.58008562f,
160.00000000f, 166.46500594f, 172.97373660f, 179.52490559f,
186.11730005f, 192.74977453f, 199.42124551f, 206.13068654f,
212.87712380f, 219.65963219f, 226.47733176f, 233.32938445f,
240.21499122f, 247.13338933f, 254.08384998f, 261.06567603f,
268.07820003f, 275.12078236f, 282.19280949f, 289.29369244f,
296.42286534f, 303.57978409f, 310.76392512f, 317.97478424f,
325.21187564f, 332.47473081f, 339.76289772f, 347.07593991f,
354.41343574f, 361.77497759f, 369.16017124f, 376.56863518f,
384.00000000f, 391.45390785f, 398.93001188f, 406.42797576f,
413.94747321f, 421.48818752f, 429.04981119f, 436.63204548f,
444.23460010f, 451.85719280f, 459.49954906f, 467.16140179f,
474.84249102f, 482.54256363f, 490.26137307f, 497.99867911f,
505.75424759f, 513.52785023f, 521.31926438f, 529.12827280f,
536.95466351f, 544.79822957f, 552.65876890f, 560.53608414f,
568.42998244f, 576.34027536f, 584.26677867f, 592.20931226f,
600.16769996f, 608.14176943f, 616.13135206f, 624.13628279f,
632.15640007f, 640.19154569f, 648.24156472f, 656.30630539f,
664.38561898f, 672.47935976f, 680.58738488f, 688.70955430f,
696.84573069f, 704.99577935f, 713.15956818f, 721.33696754f,
729.52785023f, 737.73209140f, 745.94956849f, 754.18016116f,
762.42375127f, 770.68022275f, 778.94946161f, 787.23135586f,
795.52579543f, 803.83267219f, 812.15187982f, 820.48331383f,
828.82687147f, 837.18245171f, 845.54995518f, 853.92928416f,
862.32034249f, 870.72303558f, 879.13727036f, 887.56295522f,
896.00000000f, 904.44831595f, 912.90781569f, 921.37841320f,
929.86002376f, 938.35256392f, 946.85595152f, 955.37010560f,
963.89494641f, 972.43039537f, 980.97637504f, 989.53280911f,
998.09962237f, 1006.67674069f, 1015.26409097f, 1023.86160116f,
1032.46920021f, 1041.08681805f, 1049.71438560f, 1058.35183469f,
1066.99909811f, 1075.65610955f, 1084.32280357f, 1092.99911564f,
1101.68498204f, 1110.38033993f, 1119.08512727f, 1127.79928282f,
1136.52274614f, 1145.25545758f, 1153.99735821f, 1162.74838989f,
1171.50849518f, 1180.27761738f, 1189.05570047f, 1197.84268914f,
1206.63852876f, 1215.44316535f, 1224.25654560f, 1233.07861684f,
1241.90932703f, 1250.74862473f, 1259.59645914f, 1268.45278005f,
1277.31753781f, 1286.19068338f, 1295.07216828f, 1303.96194457f,
1312.85996488f, 1321.76618236f, 1330.68055071f, 1339.60302413f,
1348.53355734f, 1357.47210556f, 1366.41862452f, 1375.37307041f,
1384.33539991f, 1393.30557020f, 1402.28353887f, 1411.26926400f,
1420.26270412f, 1429.26381818f, 1438.27256558f, 1447.28890615f,
1456.31280014f, 1465.34420819f, 1474.38309138f, 1483.42941118f,
1492.48312945f, 1501.54420843f, 1510.61261078f, 1519.68829949f,
1528.77123795f, 1537.86138993f, 1546.95871952f, 1556.06319119f,
1565.17476976f, 1574.29342040f, 1583.41910860f, 1592.55180020f,
1601.69146137f, 1610.83805860f, 1619.99155871f, 1629.15192882f,
1638.31913637f, 1647.49314911f, 1656.67393509f, 1665.86146266f,
1675.05570047f, 1684.25661744f, 1693.46418280f, 1702.67836605f,
1711.89913698f, 1721.12646563f, 1730.36032233f, 1739.60067768f,
1748.84750254f, 1758.10076802f, 1767.36044551f, 1776.62650662f,
1785.89892323f, 1795.17766747f, 1804.46271172f, 1813.75402857f,
1823.05159087f, 1832.35537170f, 1841.66534438f, 1850.98148244f,
1860.30375965f, 1869.63214999f, 1878.96662767f, 1888.30716711f,
1897.65374295f, 1907.00633003f, 1916.36490342f, 1925.72943838f,
1935.09991037f, 1944.47629506f, 1953.85856831f, 1963.24670620f,
1972.64068498f, 1982.04048108f, 1991.44607117f, 2000.85743204f,
2010.27454072f, 2019.69737440f, 2029.12591044f, 2038.56012640f
// lookup table for small values of int*log2(int) * (1 << LOG_2_PRECISION_BITS).
// Obtained in Python with:
// a=[ "%d"%i if i<(1<<32) else "%dull"%i
// for i in [ round((1<<LOG_2_PRECISION_BITS)*math.log2(i)*i) if i
// else 0 for i in range(256)]]
// print(',\n '.join([','.join(v) for v in batched([i.rjust(15)
// for i in a],4)]))
const uint64_t kSLog2Table[LOG_LOOKUP_IDX_MAX] = {
0, 0, 16777216, 39886887,
67108864, 97388723, 130105423, 164848600,
201326592, 239321324, 278663526, 319217973,
360874141, 403539997, 447137711, 491600606,
536870912, 582898099, 629637592, 677049776,
725099212, 773754010, 822985323, 872766924,
923074875, 973887230, 1025183802, 1076945958,
1129156447, 1181799249, 1234859451, 1288323135,
1342177280, 1396409681, 1451008871, 1505964059,
1561265072, 1616902301, 1672866655, 1729149526,
1785742744, 1842638548, 1899829557, 1957308741,
2015069397, 2073105127, 2131409817, 2189977618ull,
2248802933ull, 2307880396ull, 2367204859ull, 2426771383ull,
2486575220ull, 2546611805ull, 2606876748ull, 2667365819ull,
2728074942ull, 2789000187ull, 2850137762ull, 2911484006ull,
2973035382ull, 3034788471ull, 3096739966ull, 3158886666ull,
3221225472ull, 3283753383ull, 3346467489ull, 3409364969ull,
3472443085ull, 3535699182ull, 3599130679ull, 3662735070ull,
3726509920ull, 3790452862ull, 3854561593ull, 3918833872ull,
3983267519ull, 4047860410ull, 4112610476ull, 4177515704ull,
4242574127ull, 4307783833ull, 4373142952ull, 4438649662ull,
4504302186ull, 4570098787ull, 4636037770ull, 4702117480ull,
4768336298ull, 4834692645ull, 4901184974ull, 4967811774ull,
5034571569ull, 5101462912ull, 5168484389ull, 5235634615ull,
5302912235ull, 5370315922ull, 5437844376ull, 5505496324ull,
5573270518ull, 5641165737ull, 5709180782ull, 5777314477ull,
5845565671ull, 5913933235ull, 5982416059ull, 6051013057ull,
6119723161ull, 6188545324ull, 6257478518ull, 6326521733ull,
6395673979ull, 6464934282ull, 6534301685ull, 6603775250ull,
6673354052ull, 6743037185ull, 6812823756ull, 6882712890ull,
6952703725ull, 7022795412ull, 7092987118ull, 7163278025ull,
7233667324ull, 7304154222ull, 7374737939ull, 7445417707ull,
7516192768ull, 7587062379ull, 7658025806ull, 7729082328ull,
7800231234ull, 7871471825ull, 7942803410ull, 8014225311ull,
8085736859ull, 8157337394ull, 8229026267ull, 8300802839ull,
8372666477ull, 8444616560ull, 8516652476ull, 8588773618ull,
8660979393ull, 8733269211ull, 8805642493ull, 8878098667ull,
8950637170ull, 9023257446ull, 9095958945ull, 9168741125ull,
9241603454ull, 9314545403ull, 9387566451ull, 9460666086ull,
9533843800ull, 9607099093ull, 9680431471ull, 9753840445ull,
9827325535ull, 9900886263ull, 9974522161ull, 10048232765ull,
10122017615ull, 10195876260ull, 10269808253ull, 10343813150ull,
10417890516ull, 10492039919ull, 10566260934ull, 10640553138ull,
10714916116ull, 10789349456ull, 10863852751ull, 10938425600ull,
11013067604ull, 11087778372ull, 11162557513ull, 11237404645ull,
11312319387ull, 11387301364ull, 11462350205ull, 11537465541ull,
11612647010ull, 11687894253ull, 11763206912ull, 11838584638ull,
11914027082ull, 11989533899ull, 12065104750ull, 12140739296ull,
12216437206ull, 12292198148ull, 12368021795ull, 12443907826ull,
12519855920ull, 12595865759ull, 12671937032ull, 12748069427ull,
12824262637ull, 12900516358ull, 12976830290ull, 13053204134ull,
13129637595ull, 13206130381ull, 13282682202ull, 13359292772ull,
13435961806ull, 13512689025ull, 13589474149ull, 13666316903ull,
13743217014ull, 13820174211ull, 13897188225ull, 13974258793ull,
14051385649ull, 14128568535ull, 14205807192ull, 14283101363ull,
14360450796ull, 14437855239ull, 14515314443ull, 14592828162ull,
14670396151ull, 14748018167ull, 14825693972ull, 14903423326ull,
14981205995ull, 15059041743ull, 15136930339ull, 15214871554ull,
15292865160ull, 15370910930ull, 15449008641ull, 15527158071ull,
15605359001ull, 15683611210ull, 15761914485ull, 15840268608ull,
15918673369ull, 15997128556ull, 16075633960ull, 16154189373ull,
16232794589ull, 16311449405ull, 16390153617ull, 16468907026ull,
16547709431ull, 16626560636ull, 16705460444ull, 16784408661ull,
16863405094ull, 16942449552ull, 17021541845ull, 17100681785ull
};
const VP8LPrefixCode kPrefixEncodeCode[PREFIX_LOOKUP_IDX_MAX] = {
@ -371,23 +246,19 @@ const uint8_t kPrefixEncodeExtraBitsValue[PREFIX_LOOKUP_IDX_MAX] = {
112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126
};
static float FastSLog2Slow_C(uint32_t v) {
static uint64_t FastSLog2Slow_C(uint32_t v) {
assert(v >= LOG_LOOKUP_IDX_MAX);
if (v < APPROX_LOG_WITH_CORRECTION_MAX) {
const uint64_t orig_v = v;
uint64_t correction;
#if !defined(WEBP_HAVE_SLOW_CLZ_CTZ)
// use clz if available
const int log_cnt = BitsLog2Floor(v) - 7;
const uint64_t log_cnt = BitsLog2Floor(v) - 7;
const uint32_t y = 1 << log_cnt;
int correction = 0;
const float v_f = (float)v;
const uint32_t orig_v = v;
v >>= log_cnt;
#else
int log_cnt = 0;
uint64_t log_cnt = 0;
uint32_t y = 1;
int correction = 0;
const float v_f = (float)v;
const uint32_t orig_v = v;
do {
++log_cnt;
v = v >> 1;
@ -399,11 +270,11 @@ static float FastSLog2Slow_C(uint32_t v) {
// log2(Xf) = log2(floor(Xf)) + log2(1 + (v % y) / v)
// The correction factor: log(1 + d) ~ d; for very small d values, so
// log2(1 + (v % y) / v) ~ LOG_2_RECIPROCAL * (v % y)/v
// LOG_2_RECIPROCAL ~ 23/16
correction = (23 * (orig_v & (y - 1))) >> 4;
return v_f * (kLog2fTable[v] + log_cnt) + correction;
correction = LOG_2_RECIPROCAL_FIXED * (orig_v & (y - 1));
return orig_v * (kLog2Table[v] + (log_cnt << LOG_2_PRECISION_BITS)) +
correction;
} else {
return (float)(LOG_2_RECIPROCAL * v * log((double)v));
return (uint64_t)(LOG_2_RECIPROCAL_FIXED_DOUBLE * v * log((double)v) + .5);
}
}
@ -430,8 +301,7 @@ static uint32_t FastLog2Slow_C(uint32_t v) {
if (orig_v >= APPROX_LOG_MAX) {
// Since the division is still expensive, add this correction factor only
// for large values of 'v'.
const uint64_t correction =
(uint64_t)LOG_2_RECIPROCAL_FIXED * (orig_v & (y - 1));
const uint64_t correction = LOG_2_RECIPROCAL_FIXED * (orig_v & (y - 1));
log_2 += (uint32_t)DivRound(correction, orig_v);
}
return log_2;
@ -444,30 +314,30 @@ static uint32_t FastLog2Slow_C(uint32_t v) {
// Methods to calculate Entropy (Shannon).
// Compute the combined Shanon's entropy for distribution {X} and {X+Y}
static float CombinedShannonEntropy_C(const uint32_t X[256],
const uint32_t Y[256]) {
static uint64_t CombinedShannonEntropy_C(const uint32_t X[256],
const uint32_t Y[256]) {
int i;
float retval = 0.f;
uint64_t retval = 0;
uint32_t sumX = 0, sumXY = 0;
for (i = 0; i < 256; ++i) {
const uint32_t x = X[i];
if (x != 0) {
const uint32_t xy = x + Y[i];
sumX += x;
retval -= VP8LFastSLog2(x);
retval += VP8LFastSLog2(x);
sumXY += xy;
retval -= VP8LFastSLog2(xy);
retval += VP8LFastSLog2(xy);
} else if (Y[i] != 0) {
sumXY += Y[i];
retval -= VP8LFastSLog2(Y[i]);
retval += VP8LFastSLog2(Y[i]);
}
}
retval += VP8LFastSLog2(sumX) + VP8LFastSLog2(sumXY);
retval = VP8LFastSLog2(sumX) + VP8LFastSLog2(sumXY) - retval;
return retval;
}
void VP8LBitEntropyInit(VP8LBitEntropy* const entropy) {
entropy->entropy = 0.;
entropy->entropy = 0;
entropy->sum = 0;
entropy->nonzeros = 0;
entropy->max_val = 0;
@ -485,13 +355,13 @@ void VP8LBitsEntropyUnrefined(const uint32_t* const array, int n,
entropy->sum += array[i];
entropy->nonzero_code = i;
++entropy->nonzeros;
entropy->entropy -= VP8LFastSLog2(array[i]);
entropy->entropy += VP8LFastSLog2(array[i]);
if (entropy->max_val < array[i]) {
entropy->max_val = array[i];
}
}
}
entropy->entropy += VP8LFastSLog2(entropy->sum);
entropy->entropy = VP8LFastSLog2(entropy->sum) - entropy->entropy;
}
static WEBP_INLINE void GetEntropyUnrefinedHelper(
@ -504,7 +374,7 @@ static WEBP_INLINE void GetEntropyUnrefinedHelper(
bit_entropy->sum += (*val_prev) * streak;
bit_entropy->nonzeros += streak;
bit_entropy->nonzero_code = *i_prev;
bit_entropy->entropy -= VP8LFastSLog2(*val_prev) * streak;
bit_entropy->entropy += VP8LFastSLog2(*val_prev) * streak;
if (bit_entropy->max_val < *val_prev) {
bit_entropy->max_val = *val_prev;
}
@ -536,7 +406,7 @@ static void GetEntropyUnrefined_C(const uint32_t X[], int length,
}
GetEntropyUnrefinedHelper(0, i, &x_prev, &i_prev, bit_entropy, stats);
bit_entropy->entropy += VP8LFastSLog2(bit_entropy->sum);
bit_entropy->entropy = VP8LFastSLog2(bit_entropy->sum) - bit_entropy->entropy;
}
static void GetCombinedEntropyUnrefined_C(const uint32_t X[],
@ -559,7 +429,7 @@ static void GetCombinedEntropyUnrefined_C(const uint32_t X[],
}
GetEntropyUnrefinedHelper(0, i, &xy_prev, &i_prev, bit_entropy, stats);
bit_entropy->entropy += VP8LFastSLog2(bit_entropy->sum);
bit_entropy->entropy = VP8LFastSLog2(bit_entropy->sum) - bit_entropy->entropy;
}
//------------------------------------------------------------------------------

24
src/dsp/lossless_enc_mips32.c
View File

@ -23,12 +23,12 @@
#include <stdlib.h>
#include <string.h>
static float FastSLog2Slow_MIPS32(uint32_t v) {
static uint64_t FastSLog2Slow_MIPS32(uint32_t v) {
assert(v >= LOG_LOOKUP_IDX_MAX);
if (v < APPROX_LOG_WITH_CORRECTION_MAX) {
uint32_t log_cnt, y, correction;
uint32_t log_cnt, y;
uint64_t correction;
const int c24 = 24;
const float v_f = (float)v;
uint32_t temp;
// Xf = 256 = 2^8
@ -49,13 +49,14 @@ static float FastSLog2Slow_MIPS32(uint32_t v) {
// log2(Xf) = log2(floor(Xf)) + log2(1 + (v % y) / v)
// The correction factor: log(1 + d) ~ d; for very small d values, so
// log2(1 + (v % y) / v) ~ LOG_2_RECIPROCAL * (v % y)/v
// LOG_2_RECIPROCAL ~ 23/16
// (v % y) = (v % 2^log_cnt) = v & (2^log_cnt - 1)
correction = (23 * (v & (y - 1))) >> 4;
return v_f * (kLog2fTable[temp] + log_cnt) + correction;
correction = LOG_2_RECIPROCAL_FIXED * (v & (y - 1));
return (uint64_t)v * (kLog2Table[temp] +
((uint64_t)log_cnt << LOG_2_PRECISION_BITS)) +
correction;
} else {
return (float)(LOG_2_RECIPROCAL * v * log((double)v));
return (uint64_t)(LOG_2_RECIPROCAL_FIXED_DOUBLE * v * log((double)v) + .5);
}
}
@ -82,8 +83,7 @@ static uint32_t FastLog2Slow_MIPS32(uint32_t v) {
if (v >= APPROX_LOG_MAX) {
// Since the division is still expensive, add this correction factor only
// for large values of 'v'.
const uint64_t correction =
(uint64_t)LOG_2_RECIPROCAL_FIXED * (v & (y - 1));
const uint64_t correction = LOG_2_RECIPROCAL_FIXED * (v & (y - 1));
log_2 += (uint32_t)DivRound(correction, v);
}
return log_2;
@ -227,7 +227,7 @@ static WEBP_INLINE void GetEntropyUnrefinedHelper(
bit_entropy->sum += (*val_prev) * streak;
bit_entropy->nonzeros += streak;
bit_entropy->nonzero_code = *i_prev;
bit_entropy->entropy -= VP8LFastSLog2(*val_prev) * streak;
bit_entropy->entropy += VP8LFastSLog2(*val_prev) * streak;
if (bit_entropy->max_val < *val_prev) {
bit_entropy->max_val = *val_prev;
}
@ -259,7 +259,7 @@ static void GetEntropyUnrefined_MIPS32(const uint32_t X[], int length,
}
GetEntropyUnrefinedHelper(0, i, &x_prev, &i_prev, bit_entropy, stats);
bit_entropy->entropy += VP8LFastSLog2(bit_entropy->sum);
bit_entropy->entropy = VP8LFastSLog2(bit_entropy->sum) - bit_entropy->entropy;
}
static void GetCombinedEntropyUnrefined_MIPS32(const uint32_t X[],
@ -282,7 +282,7 @@ static void GetCombinedEntropyUnrefined_MIPS32(const uint32_t X[],
}
GetEntropyUnrefinedHelper(0, i, &xy_prev, &i_prev, entropy, stats);
entropy->entropy += VP8LFastSLog2(entropy->sum);
entropy->entropy = VP8LFastSLog2(entropy->sum) - entropy->entropy;
}
#define ASM_START \

12
src/dsp/lossless_enc_sse2.c
View File

@ -237,10 +237,10 @@ static void AddVectorEq_SSE2(const uint32_t* a, uint32_t* out, int size) {
// when compared to -noasm.
#if !(defined(WEBP_HAVE_SLOW_CLZ_CTZ) || defined(__i386__) || defined(_M_IX86))
static float CombinedShannonEntropy_SSE2(const uint32_t X[256],
const uint32_t Y[256]) {
static uint64_t CombinedShannonEntropy_SSE2(const uint32_t X[256],
const uint32_t Y[256]) {
int i;
float retval = 0.f;
uint64_t retval = 0;
uint32_t sumX = 0, sumXY = 0;
const __m128i zero = _mm_setzero_si128();
@ -265,15 +265,15 @@ static float CombinedShannonEntropy_SSE2(const uint32_t X[256],
if ((mx >> j) & 1) {
const int x = X[i + j];
sumXY += x;
retval -= VP8LFastSLog2(x);
retval += VP8LFastSLog2(x);
}
xy = X[i + j] + Y[i + j];
sumX += xy;
retval -= VP8LFastSLog2(xy);
retval += VP8LFastSLog2(xy);
my &= my - 1;
}
}
retval += VP8LFastSLog2(sumX) + VP8LFastSLog2(sumXY);
retval = VP8LFastSLog2(sumX) + VP8LFastSLog2(sumXY) - retval;
return retval;
}

8
src/enc/histogram_enc.c
View File

@ -229,8 +229,6 @@ void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
static WEBP_INLINE uint64_t BitsEntropyRefine(const VP8LBitEntropy* entropy) {
uint64_t mix;
const uint64_t fixed_point_entropy =
(uint64_t)(entropy->entropy * (1ll << LOG_2_PRECISION_BITS) + .5);
if (entropy->nonzeros < 5) {
if (entropy->nonzeros <= 1) {
return 0;
@ -240,7 +238,7 @@ static WEBP_INLINE uint64_t BitsEntropyRefine(const VP8LBitEntropy* entropy) {
// distributions of these are combined.
if (entropy->nonzeros == 2) {
return DivRound(99 * ((uint64_t)entropy->sum << LOG_2_PRECISION_BITS) +
fixed_point_entropy,
entropy->entropy,
100);
}
// No matter what the entropy says, we cannot be better than min_limit
@ -260,8 +258,8 @@ static WEBP_INLINE uint64_t BitsEntropyRefine(const VP8LBitEntropy* entropy) {
uint64_t min_limit = (uint64_t)(2 * entropy->sum - entropy->max_val)
<< LOG_2_PRECISION_BITS;
min_limit =
DivRound(mix * min_limit + (1000 - mix) * fixed_point_entropy, 1000);
return (fixed_point_entropy < min_limit) ? min_limit : fixed_point_entropy;
DivRound(mix * min_limit + (1000 - mix) * entropy->entropy, 1000);
return (entropy->entropy < min_limit) ? min_limit : entropy->entropy;
}
}

7
src/enc/predictor_enc.c
View File

@ -57,7 +57,9 @@ static float PredictionCostSpatialHistogram(
// Compute the new cost if 'tile' is added to 'accumulate' but also add the
// cost of the current histogram to guide the spatial predictor selection.
// Basically, favor low entropy, locally and globally.
retval += VP8LCombinedShannonEntropy(&tile[i * 256], &accumulated[i * 256]);
retval += (float)VP8LCombinedShannonEntropy(&tile[i * 256],
&accumulated[i * 256]) /
(1ll << LOG_2_PRECISION_BITS);
}
// Favor keeping the areas locally similar.
if (mode == left_mode) retval -= kSpatialPredictorBias;
@ -541,7 +543,8 @@ static float PredictionCostCrossColor(const uint32_t accumulated[256],
// Favor low entropy, locally and globally.
// Favor small absolute values for PredictionCostSpatial
static const float kExpValue = 2.4f;
return VP8LCombinedShannonEntropy(counts, accumulated) +
return (float)VP8LCombinedShannonEntropy(counts, accumulated) /
(1ll << LOG_2_PRECISION_BITS) +
PredictionCostBias(counts, 3, kExpValue);
}