Motion-Compensated Coding and Frame-Rate Up-Conversion: Models and Analysis

Block-based motion estimation (ME) and compensation (MC) techniques are widely used in modern video processing algorithms and compression systems. The great variety of video applications and devices results in numerous compression specifications. Specifically, there is a diversity of frame-rates and bit-rates. In this paper, we study the effect of frame-rate and compression bit-rate on block-based ME and MC as commonly utilized in inter-frame coding and frame-rate up conversion (FRUC). This joint examination yields a comprehensive foundation for comparing MC procedures in coding and FRUC. First, the video signal is modeled as a noisy translational motion of an image. Then, we theoretically model the motion-compensated prediction of an available and absent frames as in coding and FRUC applications, respectively. The theoretic MC-prediction error is further analyzed and its autocorrelation function is calculated for coding and FRUC applications. We show a linear relation between the variance of the MC-prediction error and temporal-distance. While the affecting distance in MC-coding is between the predicted and reference frames, MC-FRUC is affected by the distance between the available frames used for the interpolation. Moreover, the dependency in temporal-distance implies an inverse effect of the frame-rate. FRUC performance analysis considers the prediction error variance, since it equals to the mean-squared-error of the interpolation. However, MC-coding analysis requires the entire autocorrelation function of the error; hence, analytic simplicity is beneficial. Therefore, we propose two constructions of a separable autocorrelation function for prediction error in MC-coding. We conclude by comparing our estimations with experimental results

Transforms for intra prediction residuals based on prediction inaccuracy modeling

In intra video coding and image coding, the directional intra prediction is used to reduce spatial redundancy. Intra prediction residuals are encoded with transforms. In this paper, we develop transforms for directional intra prediction residuals. Specifically, we observe that the directional intra prediction is most effective in smooth regions and edges with a particular direction. In the ideal case, edges can be predicted fairly accurately with an accurate prediction direction. In practice, an accurate prediction direction is hard to obtain. Based on the inaccuracy of prediction direction that arises in the design of many practical video coding systems, we can estimate the residual variance and propose a class of transforms based on the estimated variance function. The proposed method is evaluated by the energy compaction property. Experimental results show that with the proposed method, the same amount of energy in directional intra prediction residuals can be preserved with a significantly smaller number of transform coefficients

Compressive Sensing Reconstruction for Video: An Adaptive Approach Based on Motion Estimation

This paper focuses on the problem of causally reconstructing Compressive Sensing (CS) captured video. The state-of-art causal approaches usually assume the signal support is static or changing sufficiently slowly over time, where Magnetic Resonance Imaging (MRI) is widely used as a motivating example. However, such an assumption is too restrictive for many other video applications, where the signal support changes rapidly. In this paper, we propose a framework that combines Motion Estimation (ME), the Kalman Filter (KF) and CS to adapt the reconstruction process to motions in the video so that the slowly-changing assumption on the signal support is relaxed and consequently is more suitable for video reconstruction. Explicit and implicit ME are designed to provide motion aware predictions, upon which a modified KF procedure is applied. Furthermore, three CS algorithms with embedded ME and KF are developed, and theoretical analyses are conducted via reconstruction error upper bounds, to characterize the various factors that affect reconstruction accuracy. Extensive simulations utilizing actual videos are carried out and the superiority of our methods is demonstrated.This work is supported by EPSRC Research Grant EP/K033700/1; the Natural Science Foundation of China (61401018, U1334202).This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/TCSVT.2016.254007

Transforms for prediction residuals in video coding

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 135-140).Typically the same transform, the 2-D Discrete Cosine Transform (DCT), is used to compress both image intensities in image coding and prediction residuals in video coding. Major prediction residuals include the motion compensated prediction residual, the resolution enhancement residual in scalable video coding, and the intra prediction residual in intra-frame coding. The 2-D DCT is efficient at decorrelating images, but the spatial characteristics of prediction residuals can be significantly different from the spatial characteristics of images, and developing transforms that are adapted to the characteristics of prediction residuals can improve their compression efficiency. In this thesis, we explore the differences between the characteristics of images and prediction residuals by analyzing their local anisotropic characteristics and develop transforms adapted to the local anisotropic characteristics of some types of prediction residuals. The analysis shows that local regions in images have 2-D anisotropic characteristics and many regions in several types of prediction residuals have 1-D anisotropic characteristics. Based on this insight, we develop 1-D transforms for these residuals. We perform experiments to evaluate the potential gains achievable from using these transforms within the H.264 codec, and the experimental results indicate that these transforms can increase the compression efficiency of these residuals.by Fatih Kamışlı.Ph.D

Covariance analysis of motion-compensated frame differences

The second-order statistics of motion-compensated frame differences in a ion-bit-rate hybrid video coding scheme with overlapped block motion compensation are investigated, Based on the empirical covariance sequence, an adequate compound covariance model is developed. The prediction gain for motion-compensated frame differences is evaluated, and the performance of the discrete cosine transform for interframe transform coding is discussed