Fusion of Polarization Image Based on Contourlet Transform

De Xiang Zhang; Hong Hai Wang; Jing Jing Zhang

doi:10.4028/www.scientific.net/AMM.701-702.308

Paper Titles

An Improved Hybrid Median-Mean Filter Algorithm
p.288

Background Subtraction Based on Pulse Coupled Neural Network
p.293

Detection Experiment Research of Harmonic Current for Single-Phase Active Power Filter
p.297

Extraction of Ocean Fronts Based on Empirical Mode Decomposition
p.303

Fusion of Polarization Image Based on Contourlet Transform
p.308

Image Segmentation Based on Superpixels and Saliency
p.312

Key Techniques of Fast Photographic Geological Logging in Exploration Tunnel
p.316

Quick Median Filtering Algorithms Based on FPGA
p.325

Research of Image Segmentation Based on Iterative Threshold
p.330

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 701-702Fusion of Polarization Image Based on Contourlet...

Fusion of Polarization Image Based on Contourlet Transform

Abstract:

The contourlet transform is a new two-dimensional extension of the wavelet transform using multiscale and directional filter banks and has better approximation precision and better sparse description. Firstly, the magnitude of polarization image and angle of polarization image can be decomposed into low-frequency coefficients and high-frequency coefficients with multi-scales and multi-directions using the contourlet transform. For the low-frequency coefficients, the average fusion method is used. For the each directional high frequency sub-band coefficients, the larger value of region teager energy information measurement is used to select the better coefficients for fusion. At last the fused image can be obtained by utilizing inverse transform for fused contourlet coefficients. Experimental results show that the proposed algorithm works better in preserving the edges and texture information compared with the traditional image fusion algorithms.