Low Complexity H.264 Video Encoding

H.264/AVC encoder complexity is mainly due to variable block size in Intra and Inter frames. This makes H.264/AVC very difficult to implement, especially for real time applications and mobile devices. The current technological challenge is to conserve the compression capacity and quality that H.264 offers but reduce the encoding time and, therefore, the processing complexity. This paper applies machine learning technique for video encoding mode decisions and investigates ways to improve the process of generating more general low complexity H.264/AVC video encoders. The proposed H.264 encoding method decreases the complexity in the mode decision inside the Inter frames. Results show, on average, a 67.36% reduction in encoding time, a 0.2 dB decrease in PSNR, and an average bit rate increase of 0.05% for different kinds of videos and formats. KEYWORD: Low complexity H.264, Machine learning, Data mining, Inter prediction.