PROJECT TITLE :

Development of a Framework for Stereo Image Retrieval With Both Height and Planar Features

ABSTRACT:

The wide availability and increasing range of applications for high-resolution optical satellite stereo images (HrosSIs) have created a surging demand for the development of effective content-primarily based image retrieval ways. However, this is often a challenge for existing stereo image retrieval strategies since they were designed for stereo pictures collected from shut-range imaging sensors. Therefore, successful retrieval of images isn't assured given the mismatch between existing methods and also the characteristics of HrosSIs. Moreover, none of the existing remote sensing image retrieval ways takes account of the precise characteristics of HrosSIs such as the viewing range and multiview angles. This paper proposes a generic framework to exploit the unique characteristics of HrosSIs information therefore as to permit efficient and correct content-primarily based HrosSI retrieval. HrosSIs retrieval is executed by similarity matching between the options obtained from digital surface models (DSMs) and orthoimages, each extracted from the HrosSIs. Still, the significance of height data for HrosSI retrieval was investigated. A prototype system was designed and implemented for methodology validation using the ISPRS stereo benchmark check dataset. Experimental results show that the proposed techniques are efficient for HrosSI retrieval. The proposed framework is economical and suitable for spaceborne stereo images but would possibly additionally be appropriate for airborne stereo pictures still. Experimental results also show that height data alone is inefficient and unstable for HrosSI retrieval; however, a mix of height info and planar information is economical and stable.


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