Hybrid All Zero Soft Quantized Block Detection for HEVC

Abstract

Transform and quantization account for a considerable amount of computation time in video encoding process. However, there are a large number of discrete cosine transform coefficients which are finally quantized into zeros. In essence, blocks with all zero quantized coefficients do not transmit any information, but still occupy substantial unnecessary computational resources. As such, detecting all-zero block (AZB) before transform and quantization has been recognized to be an efficient approach to speed up the encoding process. Instead of considering the hard-decision quantization (HDQ) only, in this paper, we incorporate the properties of soft-decision quantization into the AZB detection. In particular, we categorize the AZB blocks into genuine AZBs (G-AZB) and pseudo AZBs (P-AZBs) to distinguish their origins. For G-AZBs directly generated from HDQ, the sum of absolute transformed difference-based approach is adopted for early termination. Regarding the classification of P-AZBs which are generated in the sense of rate-distortion optimization, the rate-distortion models established based on transform coefficients together with the adaptive searching of the maximum transform coefficient are jointly employed for the discrimination. Experimental results show that our algorithm can achieve up to 24.16% transform and quantization time-savings with less than 0.06% RD performance loss. The total encoder time saving is about 5.18% on average with the maximum value up to 9.12%. Moreover, the detection accuracy of larger TU sizes, such as and can reach to 95% on average.

Low Complexity Quantization in High Efficiency Video Coding

“…There have been numerous works focusing on the forecast of AZBs [31,32,[46][47][48][49][50][51][52][53]. In particular, Wang et al [48] proposed to detect the zero quantized coefficients with a hybrid model, which is typically designed for 4 × 4 blocks with integer DCT transform in H.264/AVC.…”

“…To better collaborate with RDOQ process in HEVC, several investigations concentrate on the detection of two types of AZBs, including the genuine AZB (G-AZB) and pseudo AZB (P-AZB) [50][51][52]. In particular, G-AZB denotes the TBs that can be quantized to AZB through the harddecision quantization.…”

“…Q sh depends on the QP , TB sizes and the coding bit-depth [2]. In G-AZB, the absolute value of l i,j should be less than 1, such that given the TB size W and quantization parameter QP , the detection threshold for individual DCT coefficient C i,j can be described as follows [31,33,[50][51][52],…”

“…The threshold T has been widely employed for the detection of the AZBs. Cui et al [50] proposed a hybrid AZB detection method for HEVC. Initially, Walsh-order Hadamard transform is employed for 4 × 4 and 8 × 8 TUs to replace the DCT, in an effort to reduce the computational complexity, and DCT is used for 16 × 16 and 32 × 32 TUs.…”

“…where W denotes the size of the TB. Subsequently, by modeling the prediction residuals with the Laplacian distribution, another threshold for G-AZB detection can be represented as follows [50], T…”