A parallel implementation of ant colony optimization
Journal of Parallel and Distributed Computing - Problems in parallel and distributed computing: Solutions based on evolutionary paradigms
Image Thresholding Using Ant Colony Optimization
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Image interpolation using wavelet based hidden Markov trees
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Wavelet-Based Image Interpolation Using a Three-Component Exponential Mixture Model
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04
Wavelet-based statistical signal processing using hidden Markovmodels
IEEE Transactions on Signal Processing
New edge-directed interpolation
IEEE Transactions on Image Processing
Ant Colony Optimization for Image Regularization Based on a Nonstationary Markov Modeling
IEEE Transactions on Image Processing
Expert Systems with Applications: An International Journal
An evolutionary image matching approach
Applied Soft Computing
Depth image enlargement using an evolutionary approach
Image Communication
Hi-index | 12.05 |
Wavelet-based image interpolation typically treats the input image as the low frequency subbands of an unknown wavelet-transformed high-resolution image, and then produces the unknown high-resolution image by estimating the wavelet coefficients of the high frequency subbands. For that, a new approach is proposed in this paper, the contribution of which are twofold. First, unlike that the conventional Gaussian mixture (GM) model only exploits the magnitude information of the wavelet coefficients, a three-component exponential mixture (TCEM) model is proposed in this paper to investigate both the magnitude information and the sign information of the wavelet coefficients. The proposed TCEM model consists of a Gaussian component, a positive exponential component and a negative exponential component. Second, to address the parameter estimation challenge of the proposed TCEM model, the ant colony optimization (ACO) technique is exploited in this paper to classify the wavelet coefficients into one of three components of the proposed TCEM model for estimating their parameters. Experiments are conducted to demonstrate that the proposed approach outperform a number of approaches developed in the literature.