Zero-quantized DCT Coefficients Research Articles

A two-stage algorithm for the early detection of zero-quantized discrete cosine transform coefficients in High Efficiency Video Coding

For High Efficiency Video Coding (HEVC) using block-based prediction, the discrete cosine transform (DCT), and quantization, a large number of DCT coefficients in a transform block (TB) are commonly found to be quantized to zero. A two-dimensional transform in HEVC is usually implemented by first applying a butterfly-based one-dimensional (1D) DCT to each row of the residual block, followed by a 1D DCT to each column. Accordingly, we propose a two-stage method for the early detection of zero-quantized DCT coefficients in this paper. In the first stage, a distribution-based method, which uses the sum of absolute differences as the threshold criterion and compares it to threshold values obtained for all columns, is employed to detect zero-quantized columns in the pixel domain prior to conducting the actual DCT. After conducting the 1D row DCT, the second detection stage, which uses the intermediate matrix resulting from the row transform as the input, is applied in the transform domain only to those columns predicted to contain non-zero coefficients. As an orthogonal transform, the 1D row DCT has a tendency to pack a large fraction of the signal energy into a relatively few coefficients. Therefore, the second stage of our algorithm is more effective than methods that conduct detection in the pixel domain, particularly for TBs greater than 8×8. Experimental results demonstrate that an HEVC encoder with our proposed two-stage algorithm can dramatically reduce unnecessary 1D row and column DCT operations compared with a standard encoder and therefore exhibits applicability to practical HEVC encoder implementation.

Adaptive selection model for detecting zero-quantized discrete cosine transform coefficients in video coding

An adaptive selection approach for advanced video coding that reduces the number of unnecessary discrete cosine transform (DCT), quantization (Q), inverse quantization (IQ), and inverse DCT (IDCT) computations is proposed. An adaptive selection approach is used to detect zero-quantized DCT (ZQDCT) coefficients since certain zero-quantized DCT coefficients of the prediction residual block are difficult to identify. The presented algorithm detects ZQDCT coefficients according to the corresponding frequency positions before implementing DCT. Therefore, redundant DCT, Q, IQ, and IDCT procedures are removed. To carry out the proposed algorithm, three sufficient conditions are assumed for deriving eight prediction modes, which are employed to select various types of DCT, Q, IQ, and IDCT implementations. The computed results indicate that the proposed algorithm is capable of reducing the number of DCT, Q, IQ, and IDCT computations compared to those required by related methods, while retaining the coding performance of the original encoder.

Zero-Quantized Inter DCT Coefficient Prediction for Real-Time Video Coding

Several algorithms were proposed to predict the zero-quantized DCT coefficients and reduce the computational complexity of transform and quantization. It is observed that these prediction algorithms achieve good performance for all-zero-quantized DCT blocks. However, the efficiency is much lower for non-all-zero-quantized DCT blocks. This paper proposes an algorithm to improve the prediction efficiency for non-all-zero-quantized DCT blocks. The proposed method extends the prediction to 1-D transforms by developing new Gaussian distribution based thresholds for 1-D transformation. Moreover, the proposed algorithm can perform the prediction on 1-D transforms in both the pixel domain and the transform domain. The prediction for the first stage of 1-D transforms is performed in the pixel domain. However, the second stage of 1-D transforms is performed in the 1-D DCT domain. Because after the first stage of 1-D transforms most energy is concentrated to a few low frequency 1-D DCT coefficients, many transforms in the second stage are skipped. Furthermore, the method fits well the traditional row and column transform structure, and it is more implementation friendly. Simulation results show that the proposed model reduces the complexity of transform and quantization more efficiently than competing techniques. In addition, it is shown that the overall video quality achieved by the proposed algorithm is comparable to the references.

Adaptive Method for Early Detecting Zero Quantized DCT Coefficients in H.264/AVC Video Encoding

In H.264/AVC video encoding, zero quantized discrete cosine transform (DCT) coefficients are quite common in low bit-rate video application. The computations of DCT and quantization can be remarkably reduced if zero quantized DCT coefficients are detected prior to DCT and quantization. Many methods have been applied to early detect most zero quantized DCT coefficients. But the detection ratios of zero quantized DCT coefficients need to be improved when quantization parameter (QP) is small. We present an adaptive method to detect zero quantized DCT coefficients. When QP exceeds a certain value, a new threshold is derived to efficiently detect the all-zero blocks (AZBs) without any video degradation. Otherwise, a concept of fourteen-zeros block (FZB), which means only two coefficients are non-zero in 16 DCT coefficients of a 4 times 4 block, is proposed. An innovative method to process FZBs is proposed to reduce the redundant computations. Experimental results show that the proposed adaptive method achieves approximately 8%-20% computational savings, compared with that of the existing methods.

Prediction of Zero Quantized DCT Coefficients in H.264/AVC Using Hadamard Transformed Information

This paper presents an efficient approach for detecting zero quantized discrete cosine transform (ZQDCT) coefficients using the sum of absolute transformed difference (SATD). Previously, all the ZQDCT prediction approaches employ the sum of absolute difference (SAD) available ahead of DCT and quantization (Q) for early detection. However, when the Hadamard transform is enabled for H.264/AVC encoding, only the SATD instead of SAD is available before DCT and Q, and all the prediction approaches can not be directly applied. To solve this problem, the Gaussian distribution is applied to study the integer 4x4 DCT coefficients in H.264/AVC and hence an adaptive scheme with multiple thresholds against SATD is derived to realize different types of DCT and Q implementations. In addition, another two SATD based sufficient conditions are proposed for early detecting zero quantized DC coefficients for the luma components encoded with the intra 16 times 16 mode and the chroma components. The experimental results demonstrate that the proposed approach can greatly reduce the DCT and Q computations and obtain almost the same rate-distortion performance as the original encoder.

Hybrid Modeling of Intra-DCT Coefficients for Real-Time Video Encoding

The two-dimensional discrete cosine transform (2-D DCT) and its subsequent quantization are widely used in standard video encoders. However, since most DCT coefficients become zeros after quantization, a number of redundant computations are performed. This paper proposes a hybrid statistical model used to predict the zeroquantized DCT (ZQDCT) coefficients for intratransform and to achieve better real-time performance. First, each pixel block at the input of DCT is decomposed into a series of mean values and a residual block. Subsequently, a statistical model based on Gaussian distribution is used to predict the ZQDCT coefficients of the residual block. Then, a sufficient condition under which each quantized coefficient becomes zero is derived from the mean values. Finally, a hybrid model to speed up the DCT and quantization calculations is proposed. Experimental results show that the proposed model can reduce more redundant computations and achieve better real-time performance than the reference in the literature at the cost of negligible video quality degradation. Experiments also show that the proposed model significantly reduces multiplications for DCT and quantization. This is particularly suitable for processors in portable devices where multiplications consume more power than additions. Computational reduction implies longer battery lifetime and energy economy.

Hybrid Model to Detect Zero Quantized DCT Coefficients in H.264

In H.264 coding, there are a large number of discrete cosine transform (DCT) coefficients of the prediction residue which are quantized to zeros. Therefore, it is desired to design a method which can early detect zero quantized DCT coefficients (ZQDCT) before implementing DCT and quantization (Q) and thus reduce redundant computations for H.264 coding. To achieve this, a hybrid model is proposed in this paper in order to predict ZQDCT coefficients. First, the Gaussian distribution is applied to study the integer DCT coefficients in H.264 and hence an adaptive scheme with multiple thresholds is derived to realize different types of DCT and Q implementations. Then the adaptive scheme is further optimized by considering a more efficient condition to sufficiently detect all-zero DCT blocks. As a result, a hybrid model is developed. Compared with other methods in the literature, the proposed hybrid model is able to detect more ZQDCT coefficients and hence reduce more computations for H.264 encoding. It is shown by experimental results that the proposed hybrid model can achieve the best performance in reducing computations and obtain almost the same rate-distortion (R-D) performance as the original encoder in the H.264 reference software JM9.5

Efficient predictive model of zero quantized DCT coefficients for fast video encoding

Discrete cosine transform (DCT), quantization (Q), inverse quantization (IQ) and inverse DCT (IDCT) are the building blocks in video coding standards adopted by ITU-T and MEPG. Under these standards, a lot of computations are required to perform the DCT, Q, IQ and IDCT operations. With this concern, a novel statistical model based on Gaussian distribution is proposed to predict zero quantized DCT (ZQDCT) coefficients in order to reduce the computational complexity of video encoding. Compared with other predictive models in the literature, the proposed model can detect more ZQDCT coefficients. Simulation results demonstrate that the proposed statistical model is superior to others in terms of speeding up video encoders. Moreover, a hybrid model is derived based on the proposed statistical model and mathematical analysis of individual DCT coefficients to further improve the encoding efficiency.