2026-09-19T23:44:30Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/301812022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Frédo Durand.
Su, Sara Lee, 1982-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-03-24T18:27:12Z
2006-03-24T18:27:12Z
2005
2005
http://hdl.handle.net/1721.1/30181
60679664
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.
Includes bibliographical references (p. 65-70).
Applying selective emphasis to photographs is a critical aspect of the visual design process. There is evidence from psychophysics that contrast in texture is a key contributor to saliency in an image, yet unlike other low-level perceptual features, texture cannot be directly modified with existing image-processing software. We present a post-processing technique to subtly change the salience of regions of an image by modifying spatial variation in texture. Our method is inspired by computational models of visual attention that capture sensitivity to outliers in local feature distributions. We use the steerable pyramid, which encodes multi-scale oriented image features and compute a set of power maps which capture the local texture content at each scale and orientation. With this representation, texture variation can be modified to selectively add or remove emphasis in the image. Two user studies provide qualitative and quantitative psychophysical validation of our approach.
by Sara Lee Su.
S.M.
70 p.
4947146 bytes
4954249 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Perceptual picture emphasis using texture power maps
Thesis
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<Abstract>Applying selective emphasis to photographs is a critical aspect of the visual design process. There is evidence from psychophysics that contrast in texture is a key contributor to saliency in an image, yet unlike other low-level perceptual features, texture cannot be directly modified with existing image-processing software. We present a post-processing technique to subtly change the salience of regions of an image by modifying spatial variation in texture. Our method is inspired by computational models of visual attention that capture sensitivity to outliers in local feature distributions. We use the steerable pyramid, which encodes multi-scale oriented image features and compute a set of power maps which capture the local texture content at each scale and orientation. With this representation, texture variation can be modified to selectively add or remove emphasis in the image. Two user studies provide qualitative and quantitative psychophysical validation of our approach.</Abstract>
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