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Significance of perceptually relevant image decolorization for scene classification

Publication Type : Journal Article

Publisher : Journal of Electronic Imaging

Source : Journal of Electronic ImagingJournal of Electronic Imaging, Volume 26, Issue 6, p.063019 (IF: 0.780, CiteScore: 2.0, Q3- 46 percentile) (2017)

Url : https://doi.org/10.1117/1.JEI.26.6.063019

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Electronics and Communication

Year : 2017

Abstract : Color images contain luminance and chrominance components representing the intensity and color information, respectively. The objective of this paper is to show the significance of incorporating chrominance information to the task of scene classification. An improved color-to-grayscale image conversion algorithm that effectively incorporates chrominance information is proposed using the color-to-gray structure similarity index and singular value decomposition to improve the perceptual quality of the converted grayscale images. The experimental results based on an image quality assessment for image decolorization and its success rate (using the Cadik and COLOR250 datasets) show that the proposed image decolorization technique performs better than eight existing benchmark algorithms for image decolorization. In the second part of the paper, the effectiveness of incorporating the chrominance component for scene classification tasks is demonstrated using a deep belief network-based image classification system developed using dense scale-invariant feature transforms. The amount of chrominance information incorporated into the proposed image decolorization technique is confirmed with the improvement to the overall scene classification accuracy. Moreover, the overall scene classification performance improved by combining the models obtained using the proposed method and conventional decolorization methods.

Cite this Research Publication : Sowmya V., Divakaran, G., and Dr. Soman K. P., “Significance of perceptually relevant image decolorization for scene classification”, Journal of Electronic ImagingJournal of Electronic Imaging, vol. 26, no. 6, pp. 063019 (IF: 0.780, CiteScore: 2.0, Q3- 46 percentile), 2017.

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