Image processing device and method, data processing device and method, program, and recording medium

Abstract

A tentative eigenprojection matrix (#-) is provisionally generated from a studying image group (#) including a pair of a high quality image and a low quality image, and a tentative projection core tensor (#-) defining a correspondence between the low quality image and an intermediate eigenspace and a correspondence between the high quality image and the intermediate eigenspace is created. A first sub-core tensor is created from the tentative projection core tensor based on a first setting (#-), and the studying image group is projected based on the tentative eigenprojection matrix and the first sub-core tensor (#-) to calculate an intermediate eigenspace coefficient vector (#-). A representative intermediate eigenspace coefficient vector (#-) is obtained from the coefficient vector group according to the number of studying representatives, an eigenprojection matrix (#) and a projection core tensor (#) are recreated based on the determined representative studying image group (#-), and the matrix and the tensor are used in a restoration step. This can reduce the redundancy of a studying image set, reduce processing load of projection conversion, speed up a process, and suppress a memory size.