Video coding using closed-loop texture analysis and synthesis

Abstract

The compression of video content containing high-frequency textures using the Mean Squared Error (MSE) criterion or other similar distortion measures typically leads to very large bit rate assignments to these areas. However, we assume that the exact reproduction (in an MSE sense) is subjectively not required and that other measures and coding methods can be used leading to substantially lower bit rate assignments. One such measure is a global similarity measure and we demonstrate its suitability for assessing the distortion of such textures in the context of video coding. The above-mentioned concept is adapted to a new, generic, and fully automated video coding scheme that provides a texture analyzer at the encoder and a texture synthesizer at the decoder. The texture analyzer thereby identifies the target textures, where it is assumed that the viewer perceives the semantic meaning of the displayed texture rather than the specific details therein. The texture synthesizer regenerates an approximate version of the original texture based on corresponding meta data transmitted by the encoder. The texture itself is not coded in the sense of minimizing MSE or other similar distortion measures. The new approacch is integrated into an H.264/AVC video codec and yields bit rate reductions of up to 41% when compared at the same visual quality to a reference H.264/AVC codec.