Fast Mode Decision Methods in H.264/AVC Standard
| dc.contributor.author | Ganguly, Amrita | |
| dc.date.accessioned | 2015-09-16T09:50:31Z | |
| dc.date.accessioned | 2023-10-20T07:26:30Z | |
| dc.date.available | 2015-09-16T09:50:31Z | |
| dc.date.available | 2023-10-20T07:26:30Z | |
| dc.date.issued | 2011 | |
| dc.description | Supervisor: Anil Mahanta | en_US |
| dc.description.abstract | The H.264/AVC video coding standard oDers signiDcantly improved compression eD- ciency and Dexibility compared to previous standards. H.264/AVC provides better video at a lower bit rate and this translates into lesser storage requirement. H.264/AVC com- pression makes it possible to transmit HD television over a limited-capacity broadcast channel. H.264/AVC is a sophisticated compression method. However, for all its advan- tages, it must be acknowledged that it requires more processing power to encode video with H.264/AVC as compared to the previous standards. The standard is complex and its implementation is more challenging. The computationally expensive H.264/AVC coder can lead to higher encoding and decoding times. This thesis presents some new methods for reduction of the encoding time and the complexity of the H.264/ AVC encoder. A detailed study of the intra and inter prediction processes was carried out. Based on the observations gleaned from this study, a number of fast mode decision algorithms are proposed in the spatial domain and in the transform domain. Natural videos have objects with strong edges. Homogeneous region in a frame can be detected from the edges in it. This characteristic of the video is utilized for a new algorithm for intra and inter prediction process based on the edge histogram characteristic of the image. The reduction in complexity is achieved by selecting only a few coding modes from the total available modes depending upon the edge histogram characteristics and the homogeneity of the image. There are many regions in a video that are stationary. These regions generally get encoded in the SKIP mode. SKIP mode is simple to compute and if this mode can be detected prior to performing the inter prediction process, large computational saving is possible in the encoder. Thus, a low complexity algorithm is developed by predicting the \skipped"" macroblocks prior to motion estimation through early detection of the zero quantized coeDcients. A weighted prediction algorithm is next proposed that identiDes a macroblock based on certain parameters. Weights are assigned for these parameters and the encoding modes are selected accordingly. These algorithms are developed in the spatial domain. Transform domain based fast encoding algorithms are proposed where the statistics of the quantized transform coeDcients are utilized for the mode decision process. The energy of the transform coeDcients are usually concentrated in the low fequency compo- nents. An algorithm is proposed where the decision is taken from the study of the low frequency coeDcients of a block. Finally, a Subband/DCT based fast encoding algorithm is developed for H.264/AVC where the wavelet decomposition of the input image is uti- lized for the fast mode decision process. This concept is also used in a method for fast intra prediction in Scalable Video Coding. Simulation results show that the algorithms achieve signiDcant savings in complexity with a negligible loss in rate-distortion performance. Subjective evaluations show that these techniques result in similar perceptual quality when compared to a reference encoder JM12.4 of the H.264/AVC. These algorithms are likely to be useful in implementing real-time H.264/AVC standard encoders in low bitrate applications and for devices with restricted computational capability.. | en_US |
| dc.identifier.other | ROLL NO.06610215 | |
| dc.identifier.uri | https://gyan.iitg.ac.in/handle/123456789/238 | |
| dc.language.iso | en | en_US |
| dc.relation.ispartofseries | TH-1067; | |
| dc.subject | ELECTRONICS AND ELECTRICAL ENGINEERING | en_US |
| dc.title | Fast Mode Decision Methods in H.264/AVC Standard | en_US |
| dc.type | Thesis | en_US |