Bit Allocation For Video Coding Research Articles

Convex Optimization-Based Bit Allocation for Video Coding

This paper presents a new convex optimization-based bit allocation framework for video coding. Motivated by the statistical analysis of the relationship between the rate and the corresponding distortion in typical video sequences, an improved empirical rate-distortion model with more flexibility in explaining the experimental observations is proposed. The convexity and monotonicity properties of the proposed model allow us to formulate the bit allocation problem as a convex programming problem, which can be solved using interior-point methods. Coupled with the region of interest (ROI) functionality and the technique of MB classification, the proposed bit allocation scheme is then applied to the problem of frame-level bit allocation for various video coding standards employing motion compensated hybrid DCT/DPCM technique. Similar bit allocation scheme is also developed for MPEG-4 video object coding at the object level. The relevant model parameters are determined using previously encoded data by means of linear regression. Simulation results show that the proposed algorithms can achieve considerably better PSNR performance than the conventional approaches for the tested video sequences, at the expenses of slight increase in coding complexity.

Visual sensitivity guided bit allocation for video coding

A video bit allocation technique adopting a visual distortion sensitivity model for better rate-visual distortion coding control is proposed in this paper. Instead of applying complicated semantic understanding, the proposed automatic distortion sensitivity analysis process analyzes both the motion and the texture structures in the video sequences in order to achieve better bit allocation for rate-constrained video coding. The proposed technique evaluates the perceptual distortion sensitivity on a macroblock basis, and allocates fewer bits to regions permitting large perceptual distortions for rate reduction. The proposed algorithm can be incorporated into existing video coding rate control schemes to achieve same visual quality at reduced bitrate. Experiments based on H.264 JM7.6 show that this technique achieves bit-rate saving of up to 40.61%. However, the conducted subjective viewing experiments show that there is no perceptual quality degradation. EDICS-1-CPRS, 3-QUAL.

Optimised frequency-domain bit allocation for video coding

An optimal frequency domain bit allocation technique is presented. A Lagrange multiplier based approach is used for the rate-distortion optimisation of a quantisation matrix in video coding. Since the optimal quantisation matrix is heavily dependent on the choice of quantiser, the quantiser is also jointly optimised in order to alleviate the interaction between the two. The complexity of the algorithm is analysed, and it is shown to be directly proportional to the number of possible quantisation matrices and quantisation scales. Experimental results comparing the new technique with a conventional video encoder are also presented.