Robust texture retrieval of compressed images

Almost all images are stored in compressed form, most commonly in (lossy) JPEG format. In this paper, we show that compression leads to a drop in performance of texture retrieval algorithms, and propose a method that reverses this performance drop. We achieve this by what might at first glance seem counter-intuitive, namely by compressing the images even more. In particular, we recompress images (or rather re-quantising their DCT coefficients) to their lowest common image quality setting. We demonstrate, on a large benchmark texture retrieval database and using standard texture algorithms, that this results in improved image retrieval performance close to that obtained on uncompressed images.