Natural image correction by iterative projections to eigenspace constructed in normalized image space

Takeshi Shakunaga, Fumihiko Sakaue

Research output: Contribution to journalArticle

5 Citations (Scopus)


Image correction is discussed for realizing both effective object recognition and realistic image-based rendering. Three image normalizations are compared in relation with the linear subspaces and eigenspaces, and we conclude that the normalization by L1-norm, which normalizes the total sum of intensities, is the best for our purposes. Based on noise analysis in the normalized image space(NIS), an image correction algorithm is constructed, which is accomplished by iterative projections along with corrections of an image to an eigenspace in NIS. Experimental results show that the proposed method works well for natural images which include various kinds of noise shadows, reflections and occlusions. The proposed method provides a feasible solution to the object recognition based on the illumination cone [2]. The technique can also be extended to face detection of unknown person and registration/ recognition using eigenfaces.

Original languageEnglish
Pages (from-to)648-651
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
Issue number1
Publication statusPublished - Dec 1 2002


ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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