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Volume: 7 | Article ID: art00015
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Framework for an Image Sharpness Management System
Lindsay MacDonald
  DOI :  10.2352/CIC.1999.7.1.art00015  Published Online :  January 1999
Abstract

A new framework for image sharpness management is proposed, analogous to the existing framework for color management systems. Knowledge of both the human visual contrast sensitivity function (CSF) and of device spatial resolution, characterized via the modulation transfer function (MTF), can be used to determine the optimum correction to be made to the sharpness of an image for specified viewing conditions, via parametric image processing techniques. The proposed framework includes profiles for spatial input and output device characteristics, connected via a profile connection space with the facility for the operator to specify a sharpness rendering intent.Automation of Color Image ProcessingThe development of color management systems during the past decade has been driven by the following factors:Cost and productivity – When image production systems need to be automated for commercial production of images of acceptable quality, it is not cost-effective to employ a skilled person to make visual judgements for each image. Batch processing and lower skill levels are essential;Device independence – It should be possible to reproduce an image on multiple devices with the same color appearance, i.e. independent of the device or process characteristics;Inter-operability – It should be possible to preserve the color appearance of an image when transferring it from one system to another. The destination system should be able to interpret the colors in the image to produce an equivalent visual representation of the source.The same arguments justified the development of negative film printing systems in the past. More recently they have applied to desktop publishing in the graphic arts, and now they are driving the development of industry standards in digital video editing and broadcasting.All the attention so far has been on color and tonal fidelity, and standards such as those of the International Color Consortium (ICC) reflect this focus.1 Yet color and tone are not the only visual dimensions of images. Sharpness and noise are arguably of equal importance in determining the overall appearance of an image, but these have received little attention from the color imaging community. In this paper is proposed a new framework for image sharpness, which the author believes will enable new levels of image quality to be achieved economically through embedded processing within imaging systems, with a minimum of operator intervention.

Journal Title : Color and Imaging Conference
Publisher Name : Society of Imaging Science and Technology
Publisher Location : 7003 Kilworth Lane, Springfield, VA 22151, USA
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 DOI 10.2352/CIC.1999.7.1.art00015
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Lindsay MacDonald, "Framework for an Image Sharpness Management System"  in Proc. IS&T 7th Color and Imaging Conf.,  1999,  pp 75 - 79,  https://doi.org/10.2352/CIC.1999.7.1.art00015

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Copyright © Society for Imaging Science and Technology 1999
72010350
Color and Imaging Conference
color imaging conf
2166-9635
Society of Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151, USA
2166-9635(19990101)1999:1L.75;1-
cic_v1999n1/splitsection15.xml
/ist/cic/1999/00001999/00000001/art00015
Articles
Framework for an Image Sharpness Management System
MacDonaldLindsay
01011999
1999
1
75
79
1999
A new framework for image sharpness management is proposed, analogous to the existing framework for color management systems. Knowledge of both the human visual contrast sensitivity function (CSF) and of device spatial resolution, characterized via the modulation transfer function (MTF), can be used to determine the optimum correction to be made to the sharpness of an image for specified viewing conditions, via parametric image processing techniques. The proposed framework includes profiles for spatial input and output device characteristics, connected via a profile connection space with the facility for the operator to specify a sharpness rendering intent.Automation of Color Image ProcessingThe development of color management systems during the past decade has been driven by the following factors:Cost and productivity – When image production systems need to be automated for commercial production of images of acceptable quality, it is not cost-effective to employ a skilled person to make visual judgements for each image. Batch processing and lower skill levels are essential;Device independence – It should be possible to reproduce an image on multiple devices with the same color appearance, i.e. independent of the device or process characteristics;Inter-operability – It should be possible to preserve the color appearance of an image when transferring it from one system to another. The destination system should be able to interpret the colors in the image to produce an equivalent visual representation of the source.The same arguments justified the development of negative film printing systems in the past. More recently they have applied to desktop publishing in the graphic arts, and now they are driving the development of industry standards in digital video editing and broadcasting.All the attention so far has been on color and tonal fidelity, and standards such as those of the International Color Consortium (ICC) reflect this focus.1 Yet color and tone are not the only visual dimensions of images. Sharpness and noise are arguably of equal importance in determining the overall appearance of an image, but these have received little attention from the color imaging community. In this paper is proposed a new framework for image sharpness, which the author believes will enable new levels of image quality to be achieved economically through embedded processing within imaging systems, with a minimum of operator intervention.