A SIMPLE AND EFFICIENT CROSS-SENSOR RETRIEVAL METHOD FOR RETRIEVING STEREO IMAGES BY MULTISPECTRAL IMAGE
Keywords: Image Retrieval, Stereo Image, Multispectral Image, Raw Viewing Image, Probability Histogram
Abstract. Some users need to utilize a query multispectral image to quickly locate desired panchromatic stereo images from massive remotely sensed images. A stereo pair or triplet is different with a multispectral image in terms of the viewing number, viewing angle, band, radiometric resolution, spatial resolution, and ability to obtain height information. To perform the cross-sensor retrieval, the orthoimage or digital surface model (DSM) is usually produced from stereo images in a long time, drastically reducing the retrieval efficiency. To achieve a high efficiency, our study explores the potential of the raw viewing images of stereo images to be immediately used in the retrieval. We proposed a simple and efficient cross-sensor retrieval method by doing similarity matching between the query multispectral image and the raw viewing images of stereo images, using probability histograms separately produced from them. Experimental results show that our method outperformed two methods based on the orthoimage in terms of both the retrieval efficiency and precision. Our method handily deals with differences between stereo images and multispectral images, and efficiently achieves the high-accuracy cross-sensor retrieval with no need to produce the orthoimage or DSM.