Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present an improved Laplacian smoothing technique for 3D mesh denoising. This method filters directly the vertices by updating their positions. Laplacian smoothing process is simple to implement and fast, but it tends to produce shrinking and oversmoothing effects. To remedy this problem, firstly,  introduce a kernel function in the Laplacian expression. Then,  propose to use a linear combination of denoised instances. This combination aims to reduce the number of iterations of the desired method by coupling it with a technique that leads to oversmoothing. Experiments are conducted on synthetic triangular meshes corrupted by Gaussian noise. Results show that  outperform some existing methods in terms of objective and visual quality.
['Hicham Badri', 'Mohammed El Hassouni', 'Driss Aboutajdine']
I am writing a research paper on a idea Kernel-Based laplacian smoothing method for 3d mesh denoising
[{"from": "human", "value": "I am writing a research paper on a idea Kernel-Based laplacian smoothing method for 3d mesh denoising"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present an improved Laplacian smoothing technique for 3D mesh denoising. This method filters directly the vertices by updating their positions. Laplacian smoothing process is simple to implement and fast, but it tends to produce shrinking and oversmoothing effects. To remedy this problem, firstly,  introduce a kernel function in the Laplacian expression. Then,  propose to use a linear combination of denoised instances. This combination aims to reduce the number of iterations of the desired method by coupling it with a technique that leads to oversmoothing. Experiments are conducted on synthetic triangular meshes corrupted by Gaussian noise. Results show that  outperform some existing methods in terms of objective and visual quality."}]