This paper proposes to extend the Karhunen-Loeve compression algorithm to multiple images. The resulting algorithm is compared against single-image Karhunen Loeve as well as algorithms based on the Discrete Cosine Transformation (DCT). Futhermore, various methods for obtaining compressable clusters from large image databases are evaluated.
An image compression approach capable of exploiting redundancies in groups of images is introduced. The approach is based on image segmentation, texture analysis and texture synthesis. The proposed algorithm extracts textured regions from an image and merges them with similar texture data from other images, in order to take advantage of textural… (More)
—When dealing with large scale image archive systems , efficient data compression is crucial for the economic storage of data. Currently, most image compression algorithms only work on a per-picture basis — however most image databases (both private and commercial) contain high redundancies between images, especially when a lot of images of the same… (More)