A real-time computer-generated integral imaging (CGII) display rendering method based on depth-image-based multiple reference viewpoints (MDIBR) is presented, and good three-dimensional (3D) image quality with the high frame rate can be achieved. The traditional rasterization pipeline and 3D image warping are used to accelerate CGII, and the proposed method is suitable for dynamic and complex 3D content generation for the 3D display. Qualitative and quantitative experiments are carried out to evaluate the feasibility of the proposed method. Experimental results show that the MDIBR method can achieve real-time integral imaging display with 80W80 viewpoints based on large-scale 3D data with a million points.

The introduction of an attention mechanism in remote sensing image segmentation improves the accuracy of the segmentation. In this paper, a novel multi-scale KAN-based linear attention (MKLA) segmentation network of MKLANet is developed to promote a better segmentation result. A hybrid global–local attention mechanism in a feature decoder is designed to enhance the ability of aggregating the global–local context and avoiding potential blocking artifacts for feature extraction and segmentation. The local attention channel adopts MKLA block by bringing the merits of KAN convolution in Mamba like the linear attention block to improve the ability of handling linear and nonlinear feature and complex function approximation with a few extra computations. The global attention channel uses long-range cascade encoder–decoder block, where it mainly employs the 7 × 7 depth-wise convolution token mixer and lightweight 7 × 7 dilated deep convolution to capture the long-distance spatial features field and retain key spatial information. In addition, to enrich the input of the attention block, a deformable convolution module is developed between the encoder output and corresponding scale decoder, which can improve the expression ability of the segmentation model without increasing the depth of the network. The experimental results of the Vaihingen dataset (83.68% in mIoU, 92.98 in OA, and 91.08 in mF1), the UAVid dataset (69.78% in mIoU, 96.51 in OA), the LoveDA dataset (51.53% in mIoU, 86.42% in OA, and 67.19% in mF1), and the Potsdam dataset (97.14% in mIoU, 92.64% in OA, and 93.8% in mF1) outperform other advanced attention-based approaches in terms of small targets and edges’ segmentation.

Super multiview (SMV) 3D displays with a directional diffuser can provide dense viewpoints, wide viewing angles and high image quality. However, traditional SMV 3D rendering pipelines have many disadvantages, such as high time costs, low image quality, incorrect lighting effects and limited viewing angles. To overcome the abovementioned drawbacks, we propose a new SMV 3D rendering pipeline based on a hybrid rendering technique (HRT) that effectively combines and improves the Turing multiview rendering technique, the multiple view plus depth (MVD) technique and the deferred shading technique, introducing additional normal information, diffuseness information and shininess information into the SMV 3D rendering pipeline. The SMV HRT pipeline can generate SMV 3D images with accurate lighting in real time when the viewpoint number of an SMV 3D display is greater than 50, the viewing angle is greater than 100 degrees, the resolution of a single viewpoint image is more than 512*512 and the resolution of the LCD panel is 7680*4320; in particular, complex scenes can be generated in real time. The proposed HRT pipeline is the only viable real-time rendering pipeline with accurate lighting effects for super multiview 3D displays with wide viewing angle and high resolution that runs on a common PC with standard graphics hardware. An 8k SMV 3D display with an 80° viewing angle and 100 viewpoints is applied to demonstrate the validity of the HRT method in experiments. When the number of reference views is four, the experimental results show that the rendering frame rate is more than 35 fps on average for complex virtual scenes, and the peak signal-to-noise ratio (PSNR) value of the HRT is greater than 36 dB, illustrating its high image quality and accurate lighting. Compared with state-of-the-art MVD methods, HRT processes more lighting information and is more suitable for virtual scene rendering. Therefore, the HRT method has advantages regarding the image quality of the reconstructed 3D image and can easily achieve real-time rendering for SMV 3D displays with wide viewing angles.

<!-- *** Custom HTML *** --> A modified single-pass multiview rendering method is proposed to achieve real-time large viewing angle volume data three-dimensional (3-D) display. By modifying the volume rendering pipeline, the mapping of the synthetic image pixel and multiperspective information is directly accomplished in once rendering pass. And then shear-transformed ray is cast to integrate multiperspective information into the synthetic image used for 3-D display. Proof-of-concept experimental setups are constructed with the autostereoscopic 3-D display and the 3-D light-field display to demonstrate the proposed method without loss of generality. The experimental results show that the real-time frame rates of the autostereoscopic 3-D display and the 3-D light-field display are more than 30 and 60 fps at 4K (3840 × 2160) resolution, respectively. The rendering efficiency of the proposed method is irrespective of the viewpoint number and viewing angle size. In addition, it is not only compatible with the volume drawing pipeline but also robust to different types of 3-D displays based on pixel coding. A feasible way of applying 3-D display to the biological and medical fields is presented.

<!-- *** Custom HTML *** --> It is insufficiently powerful to compute multi-view images at a high enough frame or data rate to support high quality dynamic three-dimensional displays with the current computer software and hardware. According to the correspondence between lens position and elemental image, a real-time computer-generated content generation method for integral imaging based on cross perspective is presented. A GPU-driven rendering pipeline (GDRP) with geometry instancing and instance culling technique is designed, and the number of triangles processed in the rasterization stage is reduced greatly. Several virtual dynamic scenes including various materials and millions of vertices are used to verify the performance of the GDRP method in the experiment. Experimental results show that the frame rate can reach 60 fps with 3840 × 2160 resolution.