World’s Smallest h.264 Encoder
转载
http://www.cardinalpeak.com/blog/worlds-smallest-h-264-encoder/
View from the Peak

World’s Smallest h.264 Encoder
Recently I have been studying the h.264 video codec and reading the ISO spec. h.264 a much more sophisticated codec than MPEG-2, which means that a well-implemented h.264 encoder has more compression tools at its disposal than the equivalent MPEG-2 encoder. But all that sophistication comes at a price: h.264 also has a big, complicated specification with a plethora of options, many of which are not commonly used, and it takes expertise to understand which parts are important to solve a given problem.
As a bit of a parlor trick, I decided to write the simplest possible h.264 encoder. I was able to do it in about 30 lines of code—although truth in advertising compels me to admit that it doesn’t actually compress the video at all!
While I don’t want to balloon this blog post with a detailed description of h.264, a little background is in order. An h.264 stream contains the encoded video data along with various parameters needed by a decoder in order to decode the video data. To structure this data, the bitstream consists of a sequence of Network Abstraction Layer (NAL) units.
Previous MPEG specifications allowed pictures to be coded as I-frames, P-frames, or B-frames. h.264 is more complex and wonderful. It allows individual frames to be coded as multiple slices, each of which can be of type I, P, or B, or even more esoteric types. This feature can be used in creative ways to achieve different video coding goals. In our encoder we will use one slice per frame for simplicity, and we will use all I-frames.
As with previous MPEG specifications, in h.264 each slice consists of one or more 16×16 macroblocks. Each macroblock in our 4:2:0 sampling scheme contains 16×16 luma samples, and two 8×8 blocks of chroma samples. For this simple encoder, I won’t be compressing the video data at all, so the samples will be directly copied into the h.264 output.
With that background in mind, for our simplest possible encoder, there are three NALs we have to emit:
- Sequence Parameter Set (SPS): Once per stream
- Picture Parameter Set (PPS): Once per stream
- Slice Header: Once per video frame
- Slice Header information
- Macroblock Header: Once per macroblock
- Coded Macroblock Data: The actual coded video for the macroblock
Since the SPS, the PPS, and the slice header are static for this application, I was able to hand-code them and include them in my encoder as a sequence of magic bits.
Putting it all together, I came up with the following code for what I call “hello264”:
#include <stdio.h>
#include <stdlib.h>
/* SQCIF */
#define LUMA_WIDTH 128
#define LUMA_HEIGHT 96
#define CHROMA_WIDTH LUMA_WIDTH / 2
#define CHROMA_HEIGHT LUMA_HEIGHT / 2
/* YUV planar data, as written by ffmpeg */
typedef struct
{
uint8_t Y[LUMA_HEIGHT][LUMA_WIDTH];
uint8_t Cb[CHROMA_HEIGHT][CHROMA_WIDTH];
uint8_t Cr[CHROMA_HEIGHT][CHROMA_WIDTH];
} __attribute__((__packed__)) frame_t;
frame_t frame;
/* H.264 bitstreams */
const uint8_t sps[] = { 0x00, 0x00, 0x00, 0x01, 0x67, 0x42, 0x00,
0x0a, 0xf8, 0x41, 0xa2 };
const uint8_t pps[] = { 0x00, 0x00, 0x00, 0x01, 0x68, 0xce,
0x38, 0x80 };
const uint8_t slice_header[] = { 0x00, 0x00, 0x00, 0x01, 0x05, 0x88,
0x84, 0x21, 0xa0 };
const uint8_t macroblock_header[] = { 0x0d, 0x00 };
/* Write a macroblock's worth of YUV data in I_PCM mode */
void macroblock(const int i, const int j)
{
int x, y;
if (! ((i == 0) && (j == 0)))
{
fwrite(¯oblock_header, 1, sizeof(macroblock_header),
stdout);
}
for(x = i*16; x < (i+1)*16; x++)
for (y = j*16; y < (j+1)*16; y++)
fwrite(&frame.Y[x][y], 1, 1, stdout);
for (x = i*8; x < (i+1)*8; x++)
for (y = j*8; y < (j+1)*8; y++)
fwrite(&frame.Cb[x][y], 1, 1, stdout);
for (x = i*8; x < (i+1)*8; x++)
for (y = j*8; y < (j+1)*8; y++)
fwrite(&frame.Cr[x][y], 1, 1, stdout);
}
/* Write out PPS, SPS, and loop over input, writing out I slices */
int main(int argc, char **argv)
{
int i, j;
fwrite(sps, 1, sizeof(sps), stdout);
fwrite(pps, 1, sizeof(pps), stdout);
while (! feof(stdin))
{
fread(&frame, 1, sizeof(frame), stdin);
fwrite(slice_header, 1, sizeof(slice_header), stdout);
for (i = 0; i < LUMA_HEIGHT/16 ; i++)
for (j = 0; j < LUMA_WIDTH/16; j++)
macroblock(i, j);
fputc(0x80, stdout); /* slice stop bit */
}
return 0;
}
(This source code is available as a single file here.)
In main(), the encoder writes out the SPS and PPS. Then it reads YUV data from standard input, stores it in a frame buffer, and then writes out a h.264 slice header. It then loops over each macroblock in the frame and calls the macroblock() function to output a macroblock header indicating the macroblock is coded as I_PCM, and inserts the YUV data.
To use the code, you will need some uncompressed video. To generate this, I used the ffmpeg package to convert a QuickTime movie from my Kodak Zi8 video camera from h.264 to SQCIF (128×96) planar YUV format sampled at 4:2:0:
ffmpeg.exe -i angel.mov -s sqcif -pix_fmt yuv420p angel.yuv
I compile the h.264 encoder:
gcc –Wall –ansi hello264.c –o hello264
And run it:
hello264 <angel.yuv >angel.264
Finally, I use ffmpeg to copy the raw h.264 NAL units into an MP4 file:
ffmpeg.exe -f h264 -i angel.264 -vcodec copy angel.mp4
Here is the resulting output:
There you have it—a complete h.264 encoder that uses minimal CPU cycles, with output larger than its input!
The next thing to add to this encoder would be CAVLC coding of macroblocks and intra prediction. The encoder would still be lossless at this point, but there would start to be compression of data. After that, the next logical step would be quantization to allow lossy compression, and then I would add P slices. As a development methodology, I prefer to bring up a simplistic version of an application, get it running, and then add refinements iteratively.
UPDATE 4/20/11: I’ve written more about the Sequence Parameter Set (SPS) here.
Ben Mesander has more than 18 years of experience leading software development teams and implementing software. His strengths include Linux, C, C++, numerical methods, control systems and digital signal processing. His experience includes embedded software, scientific software and enterprise software development environments.
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