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In recent years, the young and expanding research community of granular computing has begun to show interest in image processing, specifically in the area of image retrieval from image databases or the Web. It might therefore be beneficial to provide a background to researchers in granular computing, at a reasonable depth, of the techniques employed in image retrieval, particularly in the case of content-based image retrieval (CBIR). This article focuses on multi-resolution image processing techniques that are commonly used in CBIR, and, in my opinion, that are potentially of interest to researchers in the area of granular computing. Given the restrictions on the length of a paper, I am unable to sufficiently address all of the important techniques in this article. Instead, I emphasize several classical techniques, and suggest several references for further reading.