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A novel optimally gamma corrected intensity span maximization approach for dark image enhancement

Publication Type : Conference Paper

Source : 22ndIEEE International Conference on Digital Signal Processing (DSP), London, United Kingdom, pp. 1-5, 2017

Url : https://www.sciencedirect.com/science/article/abs/pii/S0045790617319699

Campus : Coimbatore

School : School of Engineering

Department : Electronics and Communication

Year : 2017

Abstract : A novel image quality enhancement framework is proposed here through a collective inspiration of the exponential, differential and linear operational behavior of pixel intensities. Here, a new mask framing strategy (based on uniformity principle) is presented for harvesting the benefits of optimally ordered fractional differential (FD) unsharp masking, which is consequently counter-corrected by piecewise gamma correction (PGC) through a robustly framed weighted summation framework. PGC is imparted by the constructive involvement of reciprocal gamma values , which leads to interim compressed as well as interim expanded images. Golden-ratio rule inspired gradient-free, modified Cuckoo Search (MCS) optimization model, utilizing a newly framed Grey-Level Co-occurrence Matrix (GLCM) features based objective-function is proposed here. Experimentation highlights the outperformance of the proposed approach by desired increment in contrast, entropy, colorfulness and sharpness along with least values of correlation, energy and homogeneity, for parallel texture enhancement along with dark image enhancement.

Cite this Research Publication : H. Singh, A. Kumar, L. K. Balyan, and G. K. Singh, “A novel optimally gamma corrected intensity span maximization approach for dark image enhancement,” 22ndIEEE International Conference on Digital Signal Processing (DSP), London, United Kingdom, pp. 1-5, 2017

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