Morphological PDEs on Graphs for Image Processing on Surfaces and Point Clouds

Mesh color edit propagation aims to propagate the color from a few color strokes to the whole mesh, which is useful for mesh colorization, color enhancement and color editing, etc. Compared with image edit propagation, luminance information is not available for 3D mesh data, so the color edit propagation is more difficult on 3D meshes than images, with far less research carried out. This paper proposes a novel solution based on sparse graph regularization. Firstly, a few color strokes are interactively drawn by the user, and then the color will be propagated to the whole mesh by minimizing a sparse graph regularized nonlinear energy function. The proposed method effectively measures geometric similarity over shapes by using a set of complementary multiscale feature descriptors, and effectively controls color bleeding via a sparse 1 optimization rather than quadratic minimization used in existing work. The proposed framework can be applied for the task of interactive mesh colorization, mesh color enhancement and mesh color editing. Extensive qualitative and quantitative experiments show that the proposed method outperforms the state-of-the-art methods.

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Sparse Graph Regularized Mesh Color Edit Propagation

Ли

Lai

Rosin

2020

IEEE Trans. on Image Process.

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Morphological Operations on Unorganized Point Clouds Using Octree Graphs

Paiva¹,

Dezen-Kempter²,

Carvalho

2023

J. Comput. Cult. Herit.

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Point clouds resulting from digital scanning are increasingly being used in the heritage field to create knowledge-based models, such as building information models (BIM). Nevertheless, the use of digital image processing techniques in point cloud unorganized data is not well explored yet because of the lack of information about point adjacency and corresponding difficulty in structuring and manipulating data. In this study we propose an approach to deal with image processing-like mathematical morphological operations in unorganized point cloud using the octree graph. Our method consists of three main steps, namely: (i) computing the best distance value between points in the cloud; (ii) constructing an octree from point cloud; and (iii) producing a graph using rectangular layout. We exemplify the use of the proposed methodology performing morphological operations in grayscale and color point clouds of historical buildings. Results prove the effectiveness of the octree representation, which can efficiently generate an adjacency map, demonstrated by the resulting images, and has the potential to be applied at different areas of 3D data analysis.

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Morphological PDEs on Graphs for Image Processing on Surfaces and Point Clouds

Cited by 2 publications

References 41 publications

Sparse Graph Regularized Mesh Color Edit Propagation

Sparse Graph Regularized Mesh Color Edit Propagation

Morphological Operations on Unorganized Point Clouds Using Octree Graphs

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