A Novel Remote Sensing Image Fusion Approach Research Based on HSV Space and Bi-orthogonal Wavelet Packet Transform

Abstract

Acquiring as much spatial and spectral information as possible is a challenge of remote sensing image fusion between panchromatic (PAN) image and multispectral (MS) image. Wavelet packet analysis (WPA) can offer precise result for image process and visual characteristics of human eye are considered sufficiently in HSV (Hue, Saturation, Value) color space. A fusion approach of remote sensing images combining Region Classification and Modulus Lifting based on WPA applied in HSV color space is presented in the paper. Firstly, there can be a HSV model gained after converting the original MS image into HSV space. The Value ingredient that extracted from the HSV model is decomposed into various frequency domains via Bi-orthogonal wavelet packet transform at the third scale. The PAN image is also decomposed in the same way as the former meanwhile. Secondly, according to respective features of different frequency bands, the Region Classification rule is used in the low frequency band, and the high frequency coefficients are obtained by adopting the Modulus Lifting rule. A fused Value ingredient can be provided by inverse wavelet packet transform. Lastly, a merged image produces after finishing the space transform from HSV to RGB. By comparing with other fusion methods carefully, analysis result reveals that the proposed algorithm can achieve the most satisfactory spectrum effect and spatial information.