Near Real-Time Automatic Sub-Pixel Registration of Panchromatic and Multispectral Images for Pan-Sharpening

Guangqi Xie,Mi Wang,Luxiao He,Shao Xiang,Zhiqi Zhang

doi:10.3390/rs13183674

Abstract

This paper presents a near real-time automatic sub-pixel registration method of high-resolution panchromatic (PAN) and multispectral (MS) images using a graphics processing unit (GPU). In the first step, the method uses differential geo-registration to enable accurate geographic registration of PAN and MS images. Differential geo-registration normalizes PAN and MS images to the same direction and scale. There are also some residual misalignments due to the geometrical configuration of the acquisition instruments. These residual misalignments mean the PAN and MS images still have deviations after differential geo-registration. The second step is to use differential rectification with tiny facet primitive to eliminate possible residual misalignments. Differential rectification corrects the relative internal geometric distortion between PAN and MS images. The computational burden of these two steps is large, and traditional central processing unit (CPU) processing takes a long time. Due to the natural parallelism of the differential methods, these two steps are very suitable for mapping to a GPU for processing, to achieve near real-time processing while ensuring processing accuracy. This paper used GaoFen-6, GaoFen-7, ZiYuan3-02 and SuperView-1 satellite data to conduct an experiment. The experiment showed that our method’s processing accuracy is within 0.5 pixels. The automatic processing time of this method is about 2.5 s for 1 GB output data in the NVIDIA GeForce RTX 2080Ti, which can meet the near real-time processing requirements for most satellites. The method in this paper can quickly achieve high-precision registration of PAN and MS images. It is suitable for different scenes and different sensors. It is extremely robust to registration errors between PAN and MS.

Highlights

IntroductionPAN images and MS images [1]
From the perspective of how sensors work, remote sensing image data are split intoPAN images and MS images [1]
The spatial resolution of PAN images is high, in order to increase the intensity of the energy received, its spectral range is wider and its spectral resolution is lower than those of MS images

Summary

Introduction

PAN images and MS images [1]. The MS single-band receiving energy is weak, and the size of the detector can only be increased, resulting in the spatial resolution of an MS image being lower than that of the PAN image. The spatial resolution of PAN images is high, in order to increase the intensity of the energy received, its spectral range is wider and its spectral resolution is lower than those of MS images. A PAN image has relatively high spatial resolution, but the spectral resolution is low; an MS image data adopts a high spectral resolution, and the spatial resolution is low. A pansharpening method combines the advantages of the two: it is a process of merging a high-resolution PAN image and a lower resolution MS image to create a single high-resolution color image [2,3,4]

Methods

Results

Conclusion