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Minimalistic H264/SVC encoder single header library
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asm make asm functions visible to QEMU for profiling Oct 3, 2018
vectors add x264 sample to compare Sep 22, 2018
.gitignore initial code Sep 21, 2018
.travis.yml travis: update gcc Dec 24, 2019
LICENSE initial Sep 20, 2018
minih264e_test.c +fix aligned_alloc size argument (asan warning) Dec 24, 2019
system.c fix warnings Sep 28, 2018
system.h fix warnings Sep 28, 2018


Build Status

Small, but yet reasonably fast H264/SVC encoder single-header library with SSE/NEON optimizations. Decoder can be popped up in future.

Disclaimer: code highly experimental.

Comparison with x264

Rough comparison with x264 on an i7-6700K:

x264 -I 30 --profile baseline --preset veryfast --tune zerolatency -b 0 -r 1 --qp 33 --ipratio 1.0 --qcomp 1.0 -o x264.264 --fps 30 vectors/foreman.cif --input-res 352x288 --slices 1 --threads 1


./h264enc_x64 vectors/foreman.cif

x264 minih264
source: ~4.6mb 409kb
binary: 1.2mb 100kb
time: 0,282s 0,503s
out size: 320kb 391kb


x264:     PSNR y:32.774824 u:38.874450 v:39.926132 average:34.084281 min:31.842667 max:36.630286
minih264: PSNR y:33.321686 u:38.858879 v:39.955914 average:34.574459 min:32.389171 max:37.174073

First intra frame screenshot (left-to-right: original 152064, minih264 5067, x264 5297 bytes):

Intra screenshot

You can compare results in motion using ffplay/mpv players on vectors/out_ref.264 and vectors/x264.264 .




Minih264 supports both spatial and temporal layers. Spatial layers are almost same as encode 2 independent AVC streams except for Intra frames prediction. Following diagram shows minih264 SVC scheme for two spatial layers:

SVC diargam

That's because P frames spatial prediction are almost useless in practice. But for Intra frames there is a ~20% benefit in full resolution frame size. Note that decoder must have both base layer I frame and full resolution SVC I frame to decode whole sequence of next P frames in full resolution.


The following major features are not supported compared to x264 (baseline):

  • Trellis quantization.
  • Select prediction mode using Sum of Absolute Transform Differences (SATD).
  • 4x4 motion compensation.

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