Abstract A method of processing a digital image comprising the steps of: providing an input digital image having an input size; providing the output size of a desired output digital image; inputting the provided input digital image and the provided desired output digital image size to a weight estimation sub-system which operates to generate several weight derivative estimates; inputting the provided input digital image to an x-direction derivative estimation sub-system which produces an array of x-direction derivative estimates; inputting the provided input digital image, the weight derivative estimates and the x-direction estimates to an x-direction interpolated value estimation subsystem which produces in intermediate digital image which has the same number of rows as said input digital image while having the same number of columns as said output digital image; operating on said intermediate digital image by a y-direction derivative estimation sub-system to produce y-direction derivative estimates; inputting the intermediate digital image, the weight derivative estimates, and the y-direction derivative estimates to a y-direction interpolated value estimation sub-system to produce said output digital image.
Inventors
👤 Thaddeus F. Pawlicki
👤 Roger S. Gaborski
Bibliographic Details
Application Number—
JurisdictionUS
Data Sourcegoogle_patents
Last Synchronized2026-11-09 18:48
CPC Classifications
G; G06; G06T; G06T3/00; G06T3/40; G06T3/4007
Claims Analysis
Total Claims: 2
Claim 1
Independent Claim
209 words
A method of processing a digital image comprising the steps of: providing an input digital image having an input size; providing the output size of a desired output digital image; inputting the provided input digital image and the provided desired output digital image size to a weight estimation sub-system which operates to generate several weight derivative estimates; inputting the provided input digital image to an x-direction derivative estimation sub-system which produces an array of x-direction derivative estimates; inputting the provided input digital image, the weight derivative estimates and the x-direction estimates to an x-direction interpolated value estimation subsystem which produces in intermediate digital image which has the same number of rows as said input digital image while having the same number of columns as said output digital image; operating on said intermediate digital image by a y-direction derivative estimation sub-system to produce y-direction derivative estimates; and inputting the intermediate digital image, the weight derivative estimates, and the y-direction derivative estimates to a y-direction interpolated value estimation sub-system to produce said output digital image wherein said x-direction derivative estimation subsystem, said y-direction derivative subsystem, said x-direction interpolated value estimation subsystem, and said y-direction interpolated value estimation subsystem, respectively, use neural network universal approximators trained to emulate the rational quadratic function.
Claim 2
Independent Claim
209 words
A method of processing a digital image comprising the steps of: providing an input digital image having an input size; providing the output size of a desired output digital image; inputting the provided input digital image and the provided desired output digital image size to a weight estimation sub-system which operates to generate several weight derivative estimates; inputting the provided input digital image to an x-direction derivative estimation sub-system which produces an array of x-direction derivative estimates; inputting the provided input digital image, the weight derivative estimates and the x-direction estimates to an x-direction interpolated value estimation subsystem which produces in intermediate digital image which has the same number of rows as said input digital image while having the same number of columns as said output digital image; operating on said intermediate digital image by a y-direction derivative estimation sub-system to produce y-direction derivative estimates; and inputting the intermediate digital image, the weight derivative estimates, and the y-direction derivative estimates to a y-direction interpolated value estimation sub-system to produce said output digital image wherein said x-direction derivative estimation subsystem, said y-direction derivative subsystem, said x-direction interpolated value estimation subsystem, and said y-direction interpolated value estimation subsystem, respectively, use neural network universal approximators trained to emulate the rational quadratic function.