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The H.266/versatile video coding (VVC) standard is the most recent ITU/ISO video coding standard finalized in July 2020. VVC includes several new coding tools at different levels of the coding scheme. These coding tools enable a significant bitrate saving of up to 50% for the same subjective video quality than its predecessor H.265/high efficiency video coding (HEVC). Among these tools, we can cite the multiple transform selection (MTS) which selects at the encoder horizontal and vertical transforms among three trigonometrical transforms, including discrete cosine transform (DCT) type II, discrete sine transform (DST) type VII and DCT type VIII. Unlike the DCT-II, the DST-VII does not have efficient fast algorithmic implementation. Moreover, the MTS increases the memory usage required to store the coefficients of the three transforms. Consequently, this paper targets an efficient approximation of the DST-VII kernel based on the DCT-II and adjustment stage. The approximation of the DST-VII is modeled as an integer optimization problem jointly minimizing the error and the orthogonality of the approximate DST-VII under sparsity constraint of the adjustment stage. The sparse nonlinear optimizer (SNOPT) solver with an additional relaxation constraint is used to solve the problem and find the best sparse adjustment band matrices for different transform sizes. The DCT-VIII is then computed from the approximate DST-VII with pre/post processing operations involving only sign changes and input/output reordering. The proposed approximation provides a significant reduction in both arithmetic operations and memory usage. Moreover, it preserves the coding gain brought by the MTS under the VVC reference software. These advantages make our solution suitable for energy-efficient hardware H.266//VVC encoders and decoders deployed on consumer electronic devices. [ABSTRACT FROM AUTHOR]

Asymmetric stereoscopic video coding has already proven its effectiveness in reducing the bandwidth required for stereoscopic 3D delivery without degrading the visual quality. This approach, in which the left and right views are encoded with different levels of quality, relies on the perceptual theory of binocular suppression. However, to ensure comfortable 3D viewing, the just-noticeable level of asymmetry, i.e., the maximum quality gap between views, has to be carefully defined. Both subjectively and empirically fixed thresholds of asymmetry demonstrated either the maladjustment to content or dependency to the experimental design. This paper describes a new nonuniform asymmetric stereoscopic video coding method adaptively adjusting the level of asymmetry for each region of the image based on its perceptual significance. The proposed method uses a fully automated model that dynamically determines the best bounds of asymmetry for which the 3D viewing experience will not be altered. This is achieved by exploiting several human-visual-system-inspired models, namely, the binocular just-noticeable difference, and the visual saliency map and depth information. The simulation results show that the proposed method results in bit rate saving of up to 26% and provides better 3D visual quality compared with state-of-the-art asymmetric coding methods. [ABSTRACT FROM PUBLISHER]

Multiview video (MVV) consists of capturing the same scene with multiple cameras from different viewpoints. Therefore, substantial illumination and color inconsistencies can be observed between different views. These color mismatches can significantly reduce compression efficiency and rendering quality. In this paper, we propose a preprocessing method for correcting these color discrepancies in MVV. To consider the occlusion problem, our method is based on an improvement of histogram matching (HM) algorithm using only common regions across views. These regions are defined by an invariant feature detector (scale invariant feature transform), followed by random sample consensus algorithm to increase the matching robustness. In addition, to maintain temporal correlation, HM algorithm is applied on a temporal sliding window, allowing to cope with time-varying acquiring system, camera moving capture, and real-time broadcasting. Moreover, unlike always choosing the center view as the reference by default, we propose an automatic selection algorithm based on both views statistics and quality. The experimental results show that the proposed method increases coding efficiency with gains of up to 1.1 and 2.2 dB for the luminance and chrominance components, respectively. Furthermore, once the correction is performed, the color of real and rendered views is harmonized and looks very consistent as a whole. [ABSTRACT FROM AUTHOR]