SIFT-FANN: An efficient framework for spatio-spectral fusion of satellite images

Abstract

Image fusion techniques are widely used for remote sensing data. A special application is for using low resolution multi-spectral image with high resolution panchromatic image to obtain an image having both spectral and spatial information. Alignment of images to be fused is a step prior to image fusion. This is achieved by registering the images. This paper proposes the methods involving Fast Approximate Nearest Neighbor (FANN) for automatic registration of satellite image (reference image) prior to fusion of low spatial resolution multi-spectral QuickBird satellite image (sensed image) with high spatial resolution panchromatic QuickBird satellite image. In the registration steps, Scale Invariant Feature Transform (SIFT) is used to extract key points from both images. The keypoints are then matched using the automatic tuning algorithm, namely, FANN. This algorithm automatically selects the most appropriate indexing algorithm for the dataset. The indexed features are then matched using approximate nearest neighbor. Further, Random Sample Consensus (RanSAC) is used for further filtering to obtain only the inliers and co-register the images. The images are then fused using Intensity Hue Saturation (IHS) transform based technique to obtain a high spatial resolution multi-spectral image. The results show that the quality of fused images obtained using this algorithm is computationally efficient.

[Retracted] Multimode Intelligent Control Based on Multidata Fusion Filtering in High‐Speed Train Traffic Signal and Control

“…Information recognition carried by the Internet of vehicles requires the common realization of the same points of each model [15] Pr…”

A Review of Digital Image Fusion and its Application

“…4) In robotics applications, the fused image is mostly utilized to detect the frequency divergences in the image [75][76][77][78]. 5) It is employed in artificial neural network where a centric length according to wavelength conversion [79][80][81][82][83]. 6) Some application of image fusion deal with enhancement road map extraction which plays an important rule especially in big city in high resolution image with focusing on edge extracted by using some theory of image fusion [84].…”