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Gamma Corrected Fusion Framework of Dominant Orientation and Edge based Textural Histogram Equalization for Image Enhancement

Publication Type : Conference Paper

Source : 8thIEEE International Conference on Communication and Signal Processing (ICCSP), April 4-6, Melmaruvathur, Chennai, India, pp. 0480-0484, 2019.

Url : https://www.researchgate.net/publication/332289692_Gamma_Corrected_Fusion_Framework_of_Dominant_Orientation_and_Edge-based_Textural_Histogram_Equalization_for_Image_Enhancement

Campus : Coimbatore

School : School of Engineering

Department : Electronics and Communication

Year : 2019

Abstract : In this paper, an optimal approach is proposed for the enhancement of textural images. This objective is achieved by introducing an optimally weighted framework. It is framed by harvesting the collective benefits of gamma corrected interim channel along with dominant orientation based texture dependent interim intensity channel. In this manner both the textural features and illumination based features of the image can be improved in an efficient manner. Collective contribution of both edge-thresholding based intensity equalization and dominant-orientation based textural equalization, leads to processing of textural and edge components separately. In this paper, cuckoo search optimizer is employed for attaining the desired level of enhancement, by exploring the 2-D search space in an efficient manner. Comparative performance evaluation is presented so that the outperformance of proposed approach can be underlined.

Cite this Research Publication : P. S. Reddy, S.V.R. Kommuri, H. Singh, A. Kumar and L.K. Balyan, “Gamma Corrected Fusion Framework of Dominant Orientation and Edge based Textural Histogram Equalization for Image Enhancement,” 8thIEEE International Conference on Communication and Signal Processing (ICCSP), April 4-6, Melmaruvathur, Chennai, India, pp. 0480-0484, 2019

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