Incorporating Multiple Index Vectors and Feedback to Improve Urban Objects Retrieval

This paper reports results of integrating multiple index vectors and incorporating feedback in retrieving urban objects from high-resolution images. The integrated method combines an index vector derived from a semivariogram method and another index vector from a wavelet transform method. Results show that the integrated method notably improves retrieval precision over either method when used individually. Feedback on whether a retrieved image is relevant is subsequently incorporated into the retrieval. F-statistics is used to evaluate the ability of individual indices to identify relevant images and to weight these indices. The weighted index vector typically improves retrieval performance further by 10% to 15%.