Image Segmentation Based on the Indiscernibility Relation
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Intelligent Image Filtering Using Rough Sets
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Image resizing in the discrete cosine transform domain
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Hierarchical Neural Networks for Image Interpretation (Lecture Notes in Computer Science)
Hierarchical Neural Networks for Image Interpretation (Lecture Notes in Computer Science)
Image interpolation using neural networks
IEEE Transactions on Image Processing
New edge-directed interpolation
IEEE Transactions on Image Processing
Subpixel edge localization and the interpolation of still images
IEEE Transactions on Image Processing
Super-resolution of images based on local correlations
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
A new realtime interpolation algorithm for color image is presented. The algorithm is based on the concept of indiscernibility relation in rough sets (RS) theory. By applying the concept of upper and lower approximation based on the continuity of images, the image is first divided into homogenous area, edge pixels and isolated pixels. Then Bézier surface interpolation is further achieved using the information of classification. Besides emulation, the technology has been applied to the visual presenter with low-resolution image sensor. Results demonstrate that the new algorithm improves substantially the subjective and objective quality of the interpolated images over conventional interpolation algorithms, and meets the requirements of real time image processing. The algorithm represents an attempt to incorporate RS in image processing.