دانلود رایگان مقاله هموار سازی تصویر با گردش تصادفی تعمیم یافته

Abstract

A novel generalized random walks model based algorithm for image smoothing is presented. Unlike previous image smoothing methods, the proposed method performs image smoothing in a global weighted way based on graph notation, which can preserve important features and edges as much as possible. Based on the new random walks model, input image information and user defined smoothing scale information are projected to a graph, our method calculates the probability that a random walker starting at each pixel node position will first reach one of the pre-defined terminal node to achieve image smoothing, which goes to solving a system of linear equations, the system can be solved efficiently by lots of methods. Theoretical analysis and experimental results are reported to illustrate the usefulness and potential applicability of our algorithm on various computer vision fields, including image enhancement, edge detection, image decomposition, high dynamic range (HDR) image tone mapping and other applications.

6. Conclusion

In this work, we proposed a novel algorithm for edge preserving image smoothing. Unlike previous methods, our method has a clear physical meaning, which turned image smoothing to a random walk problem. A generalized random walks framework was proposed to solve the image smoothing problem in this paper, which provides a new perspective for the problem. Furthermore, the proposed framework has many equivalences with electric circuits, and some image processing techniques are showed to be highly related to our method, which opens the possibility for a hardware (e.g., VLSI) implementation of these algorithms. Finally, comparison with some other techniques, experiments demonstrate that our algorithm generates high quality results at low computational cost and does not suffer from some drawbacks of other previous approaches. Our future work will improve the speed of our method further and apply it into more applications.