Indeo 3

From MultimediaWiki
Jump to navigation Jump to search


Indeo Video 3 is a proprietary video compression algorithm developed by Intel. It is primarily used to encode video in AVI files. The format was commonly seen around the time of 1996 and has since been superseded by Indeo Video Interactive version 4 and 5 (see Indeo 4 and Indeo 5). There are many versions of this codec (R3.1, R3.2) but the version R3.2 (FOURCC 'IV32') is the most common. There is a support for this codec for all major platforms (Windows, Macintosh, Linux).

This document focuses on principles necessary to implement an Indeo Video 3 decoder.

Decoder specification

Coding techniques

Indeo Video 3 employs color subsampling, differential coding, vector quantization, run-lenght coding and motion compensation to achieve its compression.

Supported picture dimensions

Indeo3 has the following size restrictions:

width:  16...640 pixels
height: 16...480 pixels

All picture dimensions must be a multiple of 4.

Internal pixel format

Indeo Video 3 operates completely in the YUV color space. It uses a special downsampled case of the YVU 4:1:0 format where pixel are represented using only 7 bits. The downsampling is done in the encoder by applying the right shifting on pixel values after color conversion and subsampling. Thus, both encoder and decoder operate internally on pixel values in the range of 0-127. This was done in order to permit the software-based SIMD processing (see software vector operations).

Additionaly the upsampling is needed in the decoder. After each plane was decoded, the pixel values shall be shifted one bit left to convert them back to 8-bit values.

Software vector operations

Indeo3 is built upon the so-called "softSIMD" technique, which allows an emulation of the vector operations purely in software. As this codec was developed there was no processors equipped with a SIMD instruction set, therefore the "softSIMD" can significally boost performance.

In a processor with explicit SIMD (single instruction, multiply data) support, one operation is executed on two or more data sets to produce multiple outputs. The basic idea of the "softSIMD" is to treat the processor registers as containing multiple data words; for example, a 32-bit register can be treated as containing four 8-bit data words.

The examples below illustrate how the "softSIMD" is implemented in Indeo3:

Example 1: Adding two delta values to two pixels at once
src_pixels = 0x20202020; // predicted pixels
delta      = 0x0000FE01; // low-order bits contain two delta values: -2 and +1
dst_pixels = src_pixels + delta; // dst_pixels contains 0x20201E21 now
Example 2: Adding four delta values to four pixels at once
src_pixels = 0x20202020; // predicted pixels
delta      = 0xFE030201; // delta values: -2, +3, +2 and +1
dst_pixels = src_pixels + delta; // dst_pixels contains 0x1E232221 now
Example 3: averaging four pixels at once
dst_pixels = ((src_pixels1 + src_pixels2) >> 1) & 0x7F7F7F7F;

Internal picture representation

Each picture (frame) is divided into following pieces: planes, strips, cells and blocks.

Each frame consists of three planes: Y, V and U.

Each plane can be segmented into one or more vertical strips depends on picture width. A strip is a region of the image being encoded as self-contained section. A strip has fixed width (160 pixels for luminance and 40 pixels for chrominance). Its height is always the same as the height of the picture. Large pictures shall be encoded in several strips. This makes the encoder/decoder simplier and faster. The following example shows a typical picture segmentation (sizes are given for the luminance plane; for chrominance ones those must be divided by 4):

if the width of the image <= 160:	there is only one strip which width is <= 160
if the width of the image > 160:	there are two strips: 160 + (pic_width % 160)
if the width of the image > 320:	there are three strips: 160 + 160 + (pic_width % 320)
if the width of the image > 480:	there are four strips: 160 + 160 + 160 + (pic_width % 480)

The "%" in the examples above denotes the "MOD" operation.

Each strip is encoded with either intra-frame or inter-frame prediction. Inter-frame prediction is obtained by applying motion estimation.

Each strip will be further segmented into cells using binary tree image segmentation. Each cell consists of blocks in the raster order. All blocks in a cell share the same quantizations parameters: quantization mode and delta table index.

Available block sizes are 4x4, 4x8 and 8x8 pixels. The size of the block is determined during the encoding process according with energy of the cell. Blocks are quantized using adaptive vector quantization and the resulting bytecodes are packed into the compressed bitstream.