15. A system, comprising: a data store storing queries that were previously received from users and data identifying images that were referenced in search results responsive to the queries; and an image quality subsystem coupled to the data store, the image quality subsystem including at least one processor operable to compute, for a query, query specific quality scores for images based on initial quality scores for the images and a transformation factor for the query, the transformation factor for the query representing a measure of importance of image quality for computing relevance scores for the images for the query, the transformation factor being selected based, at least in part, on a comparison of a first number of previous user selections of high quality images for the query to a second number of previous user selections of high quality images for one or more other queries, a high quality image being an image having an initial quality score that meets a threshold score.
15. A system, comprising: a data store storing queries that were previously received from users and data identifying images that were referenced in search results responsive to the queries; and an image quality subsystem coupled to the data store, the image quality subsystem including at least one processor operable to compute, for a query, query specific quality scores for images based on initial quality scores for the images and a transformation factor for the query, the transformation factor for the query representing a measure of importance of image quality for computing relevance scores for the images for the query, the transformation factor being selected based, at least in part, on a comparison of a first number of previous user selections of high quality images for the query to a second number of previous user selections of high quality images for one or more other queries, a high quality image being an image having an initial quality score that meets a threshold score. 17. The system of claim 15 , wherein the image quality subsystem is further operable to compute initial quality scores for the images based on an image classification model that is trained based on feature vectors of positive images and negative images, the positive images being images having relevance scores for one or more queries that exceed a threshold relevance score, the negative images being images having relevance scores for one or more queries that do not exceed the threshold relevance score.