Digital image sharpening system

Abstract

A system and method for sharpening a digital image ( 38 ) having one or more image parameters, for printing with one or more print parameters, and for viewing at one or more viewing parameters, the method comprising the steps of preparing sharpening radius information correlated in a correlation process with one or more print parameters, creating a first data storage device ( 192 ) for storing the sharpening radius information, receiving the one or more print parameters, determining an image sharpening radius for the digital image ( 38 ) from the sharpening radius information and the received one or more print parameters, and sharpening the digital image ( 38 ) using the image sharpening radius in a sharpening algorithm. A correlation process is described, a sharpening algorithm with foliage protection, hue protection, antialiasing protection, and noise reduction is disclosed, and a detail identification process is described.

Description

[0001] Cross References to Related Applications [0002] This application claims U.S. Provisional Patent Application 60 / 234,270, filed September 20, 2000, entitled "System And Method For Sharpening Images," and filed December 29, 2000, entitled "System And Method For Determining OptimalSharpening Radius" U.S. Provisional Patent Application 60 / 259,017, and U.S. Provisional Patent Application 60 / 258,763, filed December 29, 2000, entitled "System And Method For Optimizing Sharpening Of Digital Images," the disclosure of each of which is at This is incorporated in its entirety for reference. technical field [0003] The present invention relates to systems and methods for optimizing the sharpening of digital images. Background technique [0004] A known problem is sharpening the image after photography to remedy blur if the image is out of focus or to simulate better film sharpness, i.e. creating the appearance that it was shot on a medium format camera when it was actually at ...

AI Technical Summary

Problems solved by technology

Simply put, sharpening in RGB results in color distortion, while sharpening in CMYK and Lab usually results in desaturated, weak halos that will negatively affect the overall appearance of the image

The third problem is that currently there is no way to reduce the noise to the extent that the image still looks natural - current existing noise reduction algorithms always make the image look unnatural

However, these methods fail to realize that the most important parameter in filtering with blur masks is actually the sharpening radius

[0012] Blur masking methods therefore have these main problems: there are three apparently independent variables, such as sharpening strength, sharpening threshold, and sharpening radius, a specific method of visual trial and error preview, in applying blur mask filtering Assuming sharpening strength is the key parameter, it is not recognized that there is a preferred sharpening radius for a given image that leads to optimal results, depending on the first choice based on printer type, printer resolution, image pixel size, and image print size. Approximation and second approximation depending on viewing distance and image detail, lack of hue preservation techniques to correct for color shifts that occur during the application of blur mask filtering, image distortion and unnatural saturation states in sharpened images, Oversharpening of detail and lack of noise reduction

Images