Sliding eigenvalue decomposition-based cross-term suppression in Wigner–Ville distribution

Singh, Vivek Kumar; Pachori, Ram Bilas

doi:10.1007/s10825-021-01781-w

Cited by 5 publications

(1 citation statement)

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“…where: 􏽥 u represents the reference template image; u represents the image to be reconstructed. us, the 3D visual feature reconstruction of interior design is realized [13][14][15].…”

Section: Visual Feature Reconstructionmentioning

confidence: 99%

Distributed 3D Environment Design System Based on Color Image Model

Huai

Zhu

et al. 2022

Mathematical Problems in Engineering

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In order to improve the effect of distributed 3D interior design, a distributed 3D interior design method based on color image model is proposed in this paper. In this paper, the author uses the distributed feature information fusion method to construct the color image model of the distributed 3D interior design, and carries out edge contour detection and feature extraction for the distributed 3D interior spatial distribution image. The RGB color decomposition method is used to decompose the color pixel features of the three-dimensional indoor spatial distribution image. Combined with the three-dimensional point cloud feature reorganization method, the color space reconstruction of the distributed three-dimensional interior design is realized, and the optimal combination of color features of the distributed three-dimensional interior design is realized. Based on the design of image and color processing algorithm, the development and design of distributed 3D interior design system is carried out based on virtual reality and visual simulation technology. The 3D modeling of distributed 3D interior design is carried out using 3ds max, and the indoor hierarchical structure design is realized using the modeling software Multigen Creator. The experimental results show that, according to the color information fusion results, the distributed 3D interior design optimization is realized. Compared with the traditional manual design method, the root mean square error of this method is greatly reduced from 0.232 to 0.023, and the time cost is 82.8% faster. This method has a better visual effect and strong feature expression ability. Conclusion. The visual effect of distributed 3D interior design with this method is good, the error is small, and the visual expression ability is strong.

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“…where: 􏽥 u represents the reference template image; u represents the image to be reconstructed. us, the 3D visual feature reconstruction of interior design is realized [13][14][15].…”

Section: Visual Feature Reconstructionmentioning

confidence: 99%