Efficient Lagrange multiplier selection algorithm for depth maps coding

Abstract

The rate-distortion optimisation criterion of depth maps coding is evaluated by virtual view distortion, which motivates research modelling the distortion and corresponding Lagrange multiplier for depth maps coding. Current studies follow the assumption that the virtual view distortion introduced by texture videos distortion and depth maps distortion can be explored separately. Then the texture-videos-distortioninduced virtual view distortion is considered as a constant value during depth maps coding. A relationship between the optimal Lagrange multiplier of depth maps and texture videos distortion is investigated. Based on this relationship, an efficient Lagrange multiplier selection algorithm is proposed for depth maps coding based on quantisation parameters of texture videos and depth maps. With the proposed Lagrange multiplier, 1.36% bitrate saving with the same virtual view quality can be achieved compared with 3D high efficiency video coding reference software.

Model‐based Lagrangian multiplier derivation method for depth map coding

“…Table 5 further gives the comparison results of the coding performance between the proposed model‐based Lagrangian multiplier method and the straight‐forward Lagrangian multiplier method in [2]. We can observe that, compared with the straight‐forward Lagrangian multiplier method in [2], an average 0.41% bitrate saving can be achieved by the proposed model‐based Lagrangian multiplier method, while maintaining the same quality of virtual views.…”

“…QP combinations for texture images and depth maps ( and ) are illustrated in Table 1. In HTM 16.0, the Lagrangian multiplier can be adjusted by a scaling factor [1, 2]. In our experiments, we first change the scaling factor to select the optimal Lagrangian multiplier for different QP combinations through the comparison of coding performance.…”

“…A novel method for depth map coding is established by involving a depth maps QP based scaling factor [1]. In [2], a straight‐forward model is built based on texture videos QP and depth maps QP. In this Letter, in order to achieve better coding performance, first, we analyse the relationships among the Lagrangian multiplier, the coding distortion, the coding bitrate and the quantisation steps of texture videos and depth maps ( and ).…”

“…Table 5 further gives the comparison results of the coding performance between the proposed model-based Lagrangian multiplier method and the straight-forward Lagrangian multiplier method in [2]. We can observe that, compared with the straight-forward Lagrangian multiplier method in [2], an average 0.41% bitrate saving can be achieved by the proposed model-based Lagrangian multiplier method, while maintaining the same quality of virtual views. The main reason for the coding performance gain is that the proposed model-based Lagrangian multiplier method in this Letter is established through the model deduction of the Lagrangian multiplier, the coding distortion, the coding bitrate and the quantisation step.…”