A Novel Video Coding Framework by Perceptual Representation and Macroblock-Based Matching Pursuit Algorithm

This paper presents a novel hybrid video coding framework by perceptual representation and macroblock-based matching pursuit algorithm (PRMBMP), which uses a set of filters to extract the perceptual parts of each video frame. The original video frame is separated into low-frequency image and high-frequency image. The low-frequency image has low sensitivity to human perception and few complex texture details, which can be handled efficiently by traditional H.264 video coding. The high-frequency image is the perceptual representation, which includes more texture details and edges. The proposed macroblock-based matching pursuit algorithm is used to compress the high-frequency image, which speeds up the conventional matching pursuit algorithm efficiently by estimating the local optimization. The experiments show that the proposed framework can achieve 2 to 3 dB improvements compared with the conventional H.264 video coding framework. The proposed framework also has the definition scalability, which can be widely used in bandwidth-variation video applications.