Ms. Chinmayi Lanka Profile

Chinmayi Lanka

at UCLA Samueli School Of Engineering

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Proceedings Article | 27 September 2016 Presentation + Paper

Novel intra prediction modes for VP10 codec

Ariel Shleifer, Chinmayi Lanka, Mohit Setia, Shubham Agarwal, Ofer Hadar, Debargha Mukherjee

Proceedings Volume 9971, 997114 (2016) https://doi.org/10.1117/12.2238140

KEYWORDS: Video compression, Video, Computer programming, Image compression, Error analysis, Cameras, Raster graphics, Quantization, Electrical engineering, Image restoration

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The demand for high quality video is permanently on the rise and with it the need for more effective compression. Compression scope can be further expanded due to increased spatial correlation of pixels within a high quality video frame. One basic feature that takes advantage of pixels’ spatial correlation for video compression is Intra-Prediction, which determines the codec’s compression efficiency. Intra-Prediction enables significant reduction of the Intra-frame (I-frame) size and, therefore, contributes to more efficient bandwidth exploitation. It has been observed that the intra frame coding efficiency of VP9 is not as good as that of H.265/MPEG-HEVC. One possible reason is that HEVC’s Intra-prediction algorithm uses as many as 35 prediction directions, while VP9 uses only 9 directions including the TM prediction mode. Therefore, there is high motivation to improve the Intra-Prediction scheme with new, original and proprietary algorithms that will enhance the overall performance of Google’s future codec and bring its performance closer to that of HEVC. In this work, instead of using different angles for predictions, we introduce four unconventional Intra-Prediction modes for the VP10 codec – Weighted CALIC (WCALIC), Intra-Prediction using System of Linear Equations (ISLE), Prediction of Discrete Cosine Transformations (PrDCT) Coefficients and Reverse Least Power of Three (RLPT). Employed on a selection eleven (11) typical images with a variety of spatial characteristics, by using Mean Square Error (MSE) evaluation criteria, we show that our proposed algorithms (modes) were preferred and thus selected around 57% of the blocks, resulting in a reduced average prediction error, i.e. the MSE of 26%. We believe that our proposed techniques will achieve higher compression without compromising video quality, thus improving the Rate-Distortion (RD) performances of the compressed video stream.

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