The 3D video extension of High Efficiency Video Coding (3D-HEVC) is the state-of-the-art video coding standard for the compression of the multiview video plus depth format. In the 3D-HEVC design, new depth-modeling modes (DMMs) are utilized together with the existing intraprediction modes for depth intracoding. The DMMs can provide more accurate prediction signals and thereby achieve better compression efficiency. However, testing the DMMs in the intramode decision process causes a drastic increase in the computational complexity. In this paper, we propose a fast mode decision algorithm for depth intracoding. The proposed algorithm first performs a simple edge classification in the Hadamard transform domain. Then, based on the edge classification results, the proposed algorithm selectively omits unnecessary DMMs in the mode decision process. Experimental results demonstrate that the proposed algorithm speeds up the mode decision process by up to 37.65% with negligible loss of coding efficiency.

Discrete Fourier transform (DFT) is the most widely used method for determining the frequency spectra of digital signals. In this paper, a 2D sliding DFT (2D SDFT) algorithm is proposed for fast implementation of the DFT on 2D sliding windows. The proposed 2D SDFT algorithm directly computes the DFT bins of the current window using the precalculated bins of the previous window. Since the proposed algorithm is designed to accelerate the sliding transform process of a 2D input signal, it can be directly applied to computer vision and image processing applications. The theoretical analysis shows that the computational requirement of the proposed 2D SDFT algorithm is the lowest among existing 2D DFT algorithms. Moreover, the output of the 2D SDFT is mathematically equivalent to that of the traditional DFT at all pixel positions.

In scalable video coding (SVC) as an extension of H.264/advanced video coding (AVC), a computationally expensive exhaustive mode decision is employed to select the best coding mode for each macroblock (MB). In order to reduce computational complexity, we propose a fast mode decision algorithm for SVC which uses an all-zero block (AZB) detection. Based on the empirical analysis of the inter-layer correlation of the AZB, the MB at the enhancement layer (EL) is predicted whether to be the AZB. Then, only predicted MBs are examined by the AZB detection algorithm. Since the mode decision can be terminated by detecting the AZB, we determine the processing order of the candidate modes at the EL in order to terminate the mode decision in the early stage. The proposed algorithm can be combined with other conventional fast mode decision methods in order to further reduce the computational complexity of those methods. Experimental results show that the proposed algorithm can significantly speed up the encoding process, especially for low bit-rate video sequences, without deteriorating the coding efficiency of SVC.

The scalable video coding (SVC) standard adopts a simple interlayer intra prediction (ILIP) method for encoding scalable video sequences. In the conventional ILIP, a prediction signal for the macroblock (MB) of the enhancement layer (EL) is obtained by simply upsampling the colocated block of the base layer (BL). We propose an improved ILIP method by generalizing the original one adopted in the SVC standard. In the proposed ILIP method, the MB of the EL is predicted using all MBs of the BL. Experimental results show that the proposed algorithm can reduce the bit rate by 1.91% to 6.44%, as compared with the conventional ILIP, while the average PSNR is not decreased.

In scalable video coding (SVC), an exhaustive mode decision is performed to search for the best mode at each macroblock. Although this method achieves an optimal trade-off between rate and distortion, it introduces an extreme computational burden on the encoder. In this letter, we propose a fast mode decision algorithm that can reduce the computational load of the mode decision for SVC. We statistically derive the expectation of the rate-distortion cost (RDcost) increase caused by skipping each mode in the mode decision. In the proposed algorithm, the encoder performs the mode decision using a small number of modes that are determined based on the expected increase of the RDcost. Experimental results show that the proposed algorithm can reduce the computational complexity significantly with negligible video quality degradation and bitrate increment.