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Cross-component chroma prediction plays an important role in improving coding efficiency for H.266/VVC. We use the differences between reference samples and the predicted sample to design an attention model for chroma prediction, namely luma difference-based chroma prediction (LDCP). Specifically, the luma differences (LDs) between reference samples and the predicted sample are employed as the input of the attention model, which is designed as a softmax function to map LDs to chroma weights nonlinearly. Finally, a weighted chroma prediction is conducted based on the weights and chroma reference samples. To provide adaptive weights, the model parameter of the softmax function can be determined based on the template (T-LDCP) or offline learning (L-LDCP), respectively. Experimental results show that the T-LDCP achieves BD-rate reductions of 0.34%, 2.02%, and 2.34% for the Y, Cb, and Cr components, and the L-LDCP brings 0.32%, 2.06%, and 2.21% BD-rate savings for Y, Cb, and Cr components, respectively. The L-LDCP introduces slight encoding and decoding time increments, i.e., 2% and 1%, when integrated into the latest VVC test model version 18.0. Besides, the LDCP can be implemented by a pixel-level parallelization which is hardware-friendly.
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Accurately calibrating an unfocused plenoptic camera is essential to its applications. Rapid progress has been made in this area in the past decades. In this paper, detailed analysis is first performed toward the state-of-the-art projection model. Based on the analysis, parameters in the projection model are divided into two groups. Then, based on the parameter analysis, a new, to the best of our knowledge, form of the projection model, together with a new image feature light field structure point (LF-structure-point), is proposed. The LF-structure-point provides a completely non-redundant representation of the signal structure of the recorded light field raw data and induces a virtual space, "light field structure space," which is related to the real physical space by a 3D-to-3D projective transformation. The extracting algorithm of the LF-structure-point is also presented. Finally, based on the 3D-to-3D projective transformation and parameter grouping, a simple two-step calibration method using the LF-structure-point as the input data is then proposed and achieves satisfactory experimental results.
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In this paper, we propose a relative pose estimation algorithm for micro-lens array (MLA)-based conventional light field (LF) cameras. First, by employing the matched LF-point pairs, we establish the LF-point-LF-point correspondence model to represent the correlation between LF features of the same 3D scene point in a pair of LFs. Then, we employ the proposed correspondence model to estimate the relative camera pose, which includes a linear solution and a non-linear optimization on manifold. Unlike prior related algorithms, which estimated relative poses based on the recovered depths of scene points, we adopt the estimated disparities to avoid the inaccuracy in recovering depths due to the ultra-small baseline between sub-aperture images of LF cameras. Experimental results on both simulated and real scene data have demonstrated the effectiveness of the proposed algorithm compared with classical as well as state-of-art relative pose estimation algorithms.
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This paper investigates the thermomechanical formation and recovery of nanometer-scale indents in a shape memory polymer (SMP), studied using a heated atomic force microscope (AFM) tip and hot-stage atomic force microscopy. The material tested is a tert-butyl acrylate (tBA)-based polymer, which has a glass transition temperature of 60 degrees C. The AFM tip forms indents in the polymer in the temperature range 25-250 degrees C. The shape recovery of the indents is studied while the polymer is heated up to 100 degrees C. The temperature required for complete annealing of the indents depends upon the indentation formation conditions, with higher temperature formation corresponding to higher temperature recovery.
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Investigations on the motion of a fluid in capillary geometries have been extensively reported in the literature using both experimental and theoretical approaches. In this paper, the theories for capillary flow are generalized to a unified nonlinear second-order differential equation which takes the effects of the entrance, the inertial forces, and the dynamic contact angle into account. An analytical solution of the differential equation is obtained in the form of a double Dirichlet series. The readily evaluated analytical solution is compared with experimental and numerical results in the literature, which shows a good agreement. It is demonstrated that this analytical approach can be used to predict capillary flows for a wide range of fluids and parallel-plate and tube geometries in a unified manner.