Reducing inverse quantization numbers in intra frame for video transcoding architectures.

Abstract

In this study, a complexity-quality analysis with transcoding architectures is proposed for reducing inverse quantization numbers. This architecture is different from conventional transcoding scheme, which neglects the relationship between previous and current quantizer step size. However, the proposed transcoding architecture depends on the modulus of the ratio of the current and previous quantization parameter. By analyzing the quantized area of the previous and current quantization parameter, we concluded the part of undoing first inverse quantization, to reduce computing complexity. From computer simulation, we verify the merits of the proposed scheme over the conventional transcoding approaches, in terms of achieving better performance based on the computing complexity and objective (e.g., the peak signal-to-noise ratio) analysis.