High Efficiency Video Coding is a new video coding standard after H.264/AVC. By introducing a flexible coding unit, which can be recursively divided from 64×64 to 8×8 blocks in a Quadtree-Structure, HEVC achieves significantly higher coding efficiency than the previous standards. With the flexible CU structure, HEVC can effectively adapt to highly varying contents with a smaller CU or to flat contents with a larger CU, making it suitable for applications from mobile video to super high definition television. On the other hand, CU division does incur high computational cost for HEVC. In this paper, we propose a simple and fast CU division algorithm by using only a subset of pixels to determine when CU division happens. Experiment results show that our algorithm can achieve prediction quality close to HEVC Test Model with much lower computational cost.

This paper introduces a new image representation method that is named the projective image representation (PIR). We consider an image as a collage of symmetric segments each of which can be well represented by its projection data of a single orientation. A quadtree-based method is adopted to decompose an image into variable sized segments according to the complexity within it. Also, we deal with the application of the PIR to the image compression and propose an efficient algorithm, the quadtree-structured projection vector quantization (QTPVQ) which combines the PIR with the VQ. As the VQ is carried out on the projection data instead of the pixel intensities of the segment, the QTPVQ successfully overcomes the drawbacks of the conventional VQ algorithms such as the blocking artifact and the difficulty in manipulating the large dimension. Above all, the QTPVQ improves the subjective quality greatly, especially at low bit rate, which makes it applicable to low bit rate image coding.