Implementation Comparison of Intra Prediction Scheme

Due to increasing demand of video application such as video conference, video communication, video streaming and storage, video compression is required. Due to this requirement new international standard H.264 & H.265 HEVC are introduce for video compression. These standards improve video compression based on intra prediction. Intra prediction is a technique to enhance compression through use of neighboring pixels to predict current coding block. Intra prediction in H.264 / AVC is executed in the spatial domain, to predict with reference to neighboring samples of previously coded blocks to the left and / or above the block. There are total nine modes used to predict the current block. This work supports 4�4 block size and 16�16 block size for the prediction of the mode. The goal of this work is to reduce the computational complexity of intra prediction and to give accurate prediction result. In this work efficient intra prediction scheme is implemented and compared to literature

An Efficient Intra Prediction Algorithm for H.264/AVC High Profile

[[abstract]]A simple, highly efficient intra prediction algorithm to reduce the computational complexity of H.264/AVC High Profile is proposed. The algorithm combines two methods. The first method is a quant-based block-size selection decision that is based on the sum of the quantization AC coefficients among intra 8 × 8 mode predictions, combined with an error adjustment to select either intra 4 × 4 or intra 16 × 16 mode predictions. The second method is a novel direction-based prediction mode decision that is used to reduce the possible prediction modes for the rate-distortion (RD) optimization technique. Our experimental results demonstrate that the proposed algorithm reduces the encoding time by approximately 54% compared with that needed for an exhaustive search using the joint model reference software. The peak signal-to-noise ratio degradation is negligible, and the bit rate increment is minimal. Furthermore, the results show that our algorithm achieves a significant improvement in both computation performance and RD performance as compared with the existing algorithms.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]電子