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Proceedings Paper

Adaptive sharpening of photos
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Paper Abstract

Sharpness is an important attribute that contributes to the overall impression of printed photo quality. Often it is impossible to estimate sharpness prior to printing. Sometimes it is a complex task for a consumer to obtain accurate sharpening results by editing a photo on a computer. The novel method of adaptive sharpening aimed for photo printers is proposed. Our approach includes 3 key techniques: sharpness level estimation, local tone mapping and boosting of local contrast. Non-reference automatic sharpness level estimation is based on analysis of variations of edges histograms, where edges are produced by high-pass filters with various kernel sizes, array of integrals of logarithm of edges histograms characterizes photo sharpness, machine learning is applied to choose optimal parameters for given printing size and resolution. Local tone mapping with ordering is applied to decrease edge transition slope length without noticeable artifacts and with some noise suppression. Unsharp mask via bilateral filter is applied for boosting of local contrast. This stage does not produce strong halo artifact which is typical for the traditional unsharp mask filter. The quality of proposed approach is evaluated by surveying observer's opinions. According to obtained replies the proposed method enhances the majority of photos.

Paper Details

Date Published: 28 January 2008
PDF: 12 pages
Proc. SPIE 6807, Color Imaging XIII: Processing, Hardcopy, and Applications, 68070U (28 January 2008); doi: 10.1117/12.758613
Show Author Affiliations
Ilia V. Safonov, Samsung Research Ctr. (Russia)
Michael N. Rychagov, Samsung Research Ctr. (Russia)
KiMin Kang, Samsung Electronics Co., Ltd. (South Korea)
Sang Ho Kim, Samsung Electronics Co., Ltd. (South Korea)


Published in SPIE Proceedings Vol. 6807:
Color Imaging XIII: Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu; Shoji Tominaga, Editor(s)

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