19. A processing system comprising: at least one processor; a non-transitory machine-accessible medium responsive to the processor; and instructions in the machine-accessible medium, wherein the instructions, when executed by the processor, enable the processing system to perform operations comprising: receiving an example image for use in querying a collection of digital images; using a local feature descriptor representing a portion of the contents of a digital image and a global feature descriptor representing substantially all of the contents of the digital image to perform a content-based image comparison of the collection of digital images with the example image, to automatically rank the collection of digital images with respect to similarity to the example image, wherein the global feature descriptor is content based; using a final classifier and multiple different intermediate classifiers to perform the automatic ranking, comprising: generating, by the different intermediate classifiers, intermediate relevance metrics with respect to different modalities; and generating, by the final classifier, results from the intermediate classifiers into a final relevance metric to display images in ranked order; after generating the final relevance metric, receiving input identifying a second example image for use in querying the collection of digital images; automatically determining at least one new intermediate classifier, based at least in part on the example images; automatically determining a new final classifier, based at least in part on the example images; and using the new intermediate classifier and the new final classifier to automatically re-rank the digital images in the collection with respect to similarity to the example images.
19. A processing system comprising: at least one processor; a non-transitory machine-accessible medium responsive to the processor; and instructions in the machine-accessible medium, wherein the instructions, when executed by the processor, enable the processing system to perform operations comprising: receiving an example image for use in querying a collection of digital images; using a local feature descriptor representing a portion of the contents of a digital image and a global feature descriptor representing substantially all of the contents of the digital image to perform a content-based image comparison of the collection of digital images with the example image, to automatically rank the collection of digital images with respect to similarity to the example image, wherein the global feature descriptor is content based; using a final classifier and multiple different intermediate classifiers to perform the automatic ranking, comprising: generating, by the different intermediate classifiers, intermediate relevance metrics with respect to different modalities; and generating, by the final classifier, results from the intermediate classifiers into a final relevance metric to display images in ranked order; after generating the final relevance metric, receiving input identifying a second example image for use in querying the collection of digital images; automatically determining at least one new intermediate classifier, based at least in part on the example images; automatically determining a new final classifier, based at least in part on the example images; and using the new intermediate classifier and the new final classifier to automatically re-rank the digital images in the collection with respect to similarity to the example images. 27. A processing system according to claim 19 , wherein the operation of using feature descriptors to automatically rank the collection of digital images comprises: using at least one similarity matrix to automatically rank the digital images.