Image compression by linear splines over adaptive triangulations
Signal Processing
An Optimisation-Based Approach to Mesh Smoothing: Reformulation and Extensions
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
Content adaptive mesh representation of images using binary space partitions
IEEE Transactions on Image Processing
A fast approach for accurate content-adaptive mesh generation
IEEE Transactions on Image Processing
Time-Varying Mesh Compression Using an Extended Block Matching Algorithm
IEEE Transactions on Circuits and Systems for Video Technology
Correction of atmospheric turbulence degraded sequences using grid smoothing
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part II
Hi-index | 0.00 |
In the past few years, mesh representation of images has attracted a lot of research interest due to its wide area of applications in image processing. In the mesh framework, an image is represented by a graph in which the nodes represent the pixels and the edges reflect the connectivity. The definition of the most adapted mesh for a given image is a challenge in terms of computation cost and information representation. In this paper, a new method for content adaptive mesh representation of gray scale images, called grid smoothing, is presented. A cost function is defined using the spatial coordinates of the nodes and the gray levels present in the image. The minimisation of the cost function leads to new spatial coordinates for each node. Using an adequate cost function, the grid is compressed in the regions with large gradient values and relaxed in the other regions. The result is a grid which better fits the objects in the image. The mathematical framework of the method is introduced in the paper. An in-depth study of the convergence is presented as well as results on real gray scale images.