Enhanced Derivation of Model Parameters for Cross-Component Linear Model (CCLM) in VVC

Abstract

Cross-component linear model (CCLM) has been recently adopted as a chroma intra-prediction tool in Versatile Video Coding (VVC), which is being developed as a new video coding standard. CCLM predicts chroma components from luma components through a linear model based on assumption of linear correlation between both components. A linear model is derived from the reconstructed neighboring luma and chroma samples of the current coding block by linear regression. A simplified linear modeling method recently adopted in the test model of VVC (VTM) 3.0 significantly reduces computational complexity of deriving model parameters with considerable coding loss. This letter proposes a method of linear modeling to compensate the coding loss of the simplified linear model. In the proposed method, the model parameters which are quite roughly derived in the existing simplified linear model are refined more accurately using individual method to derive each parameter. Experimental results show that, compared to VTM 3.0, the proposed method gives 0.08%, 0.52% and 0.55% Bjotegaard-Delta (BD)-rate savings, for Y, Cb and Cr components, respectively, in the All-Intra (AI) configuration with negligible computational complexity increase.

Fusion-Based Versatile Video Coding Intra Prediction Algorithm with Template Matching and Linear Prediction

“…In most cases, the performance of our proposed algorithm was superior to the others. In [28], Yoon et al optimized the CCLM algorithm and achieved good results, although their work only enhanced the channel correlation between the luminance and chroma components and did not consider the correlation of the stronger chroma components themselves. Therefore, overall, our algorithm performed better.…”

“…To better predict the areas with complex textures, Li et al [27] presented an improved intra prediction mode combination method and introduced an efficient mode coding method of syntax elements to enhance the coding performance. Yoon et al [28] designed a method to obtain the parameters of CCLM more precisely, which compensated for the coding loss of the simplified CCLM mode. To fully utilize the advantages of Intra Block Copy (IBC) and palette coding, Zhu et al [29] designed a compound palette mode to improve the performance of VVC on screen content coding.…”

A Novel Information Hiding Method for H.266/VVC Based on Selections of Luminance Transform and Chrominance Prediction Modes

“…H.266/VVC introduces many new compression tools to enhance the compression efficiency. For the intra prediction, H.266/VVC introduces several new mechanisms [25], such as Matrix weighted Intra Prediction (MIP) [26], Multiple reference line (MRL) [27], and Crosscomponent linear model (CCLM) [28], which increases the flexibility of mode selection, thus potentially suiting information hiding. Further, H.266/VVC designs a novel adaptive transform selection mechanism, named Multiple Transform Selection (MTS) [29], to switch between horizontal and vertical residual transforms based on the hybrid DCT+DST scheme and make the compression more effective.…”