IMAGE QUALITY ENHANCING APPARATUS, IMAGE DISPLAY APPARATUS, IMAGE QUALITY ENHANCING METHOD, AND COMPUTER READABLE STORAGE MEDIUM

摘要

An image quality enhancing apparatus, an image display apparatus, an image quality enhancing method, and a computer readable storage medium which make a learning-type image quality enhancing method utilizing a sparse expression practical are provided. The image quality enhancing apparatus calculates, from the feature quantity of an image, coefficients of low-image-quality base vectors expressing a feature quantity with a linear sum and generates the image with the enhanced image quality by calculating a linear sum of high-image-quality base vectors using the calculated coefficient. When calculating the coefficient, T base vectors highly influential on the feature quantity are selected from among a plurality of base vectors and an analytic solution making L2 norm of a coefficient matrix α as small as possible is calculated. A sparse solution of the coefficients can be obtained without using the iteration method and a practical image quality enhancing apparatus can be realized.

主权项

1. An image quality enhancing apparatus comprising:
a section which stores a plurality of first feature quantities which can express a feature quantity in any image with a linear sum thereof; a section which stores a plurality of second feature quantities which indicate a feature quantity of a high image quality corresponding to the first feature quantities; a coefficient calculating section which calculates, from a feature quantity of an image targeted for image quality enhancement, a coefficient for expressing the feature quantity with the linear sum of the plurality of first feature quantities; and a section which generates an image which is the image with the image quality enhanced by replacing each of the first feature quantities included in the linear sum using the coefficient calculated by the coefficient calculating section with corresponding second feature quantities; wherein the coefficient calculating section comprises:
a selecting section which selects fewer first feature quantities than the total number of the plurality of first feature quantities; anda calculating section which calculates a coefficient to be multiplied by the first feature quantities selected by the selecting section as a sparse solution by calculating an analytic solution without using the iteration method, based on the first feature quantities selected by the selecting section and the feature quantity of the image.