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Image Enhancement for Varying Lighting Conditions Using Color and Depth Images


Affiliations
1 NBKR Institute of Science & Technology, Vidyanagar, Nellore (Dt), Andhra Pradesh-524413, India
2 NBKR Institute of Science & Technology, Vidyanagar, Nellore (Dt), Andhra Pradesh-524413, India
     

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In this paper, we have a tendency to propose a replacement international distinction improvement algorithmic program exploitation the histograms of color and depth pictures. On the thought of the histogram-change system, the shading and profundity picture histograms region unit starting partitioning into sub interims misuse the Gaussian blend model. The positions partitioning the color histograms area unit adjusted to spatially neighbor pixels with an equivalent intensity and depth values will be sorted into an equivalent interval. By estimating the mapping curve of the distinction improvement for every interval, exploitation this model international distinction improvement will be improved while not over-enhancing the native picture qualification. Test results show the adequacy of the projected algorithmic program.

Keywords

Contrast Enhancement, Depth Image, Histogram Modification, Histogram Partitioning.
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  • Image Enhancement for Varying Lighting Conditions Using Color and Depth Images

Abstract Views: 218  |  PDF Views: 3

Authors

N. Narendra Babu
NBKR Institute of Science & Technology, Vidyanagar, Nellore (Dt), Andhra Pradesh-524413, India
C. Mohan Rao
NBKR Institute of Science & Technology, Vidyanagar, Nellore (Dt), Andhra Pradesh-524413, India
L. Guru Kumar
NBKR Institute of Science & Technology, Vidyanagar, Nellore (Dt), Andhra Pradesh-524413, India

Abstract


In this paper, we have a tendency to propose a replacement international distinction improvement algorithmic program exploitation the histograms of color and depth pictures. On the thought of the histogram-change system, the shading and profundity picture histograms region unit starting partitioning into sub interims misuse the Gaussian blend model. The positions partitioning the color histograms area unit adjusted to spatially neighbor pixels with an equivalent intensity and depth values will be sorted into an equivalent interval. By estimating the mapping curve of the distinction improvement for every interval, exploitation this model international distinction improvement will be improved while not over-enhancing the native picture qualification. Test results show the adequacy of the projected algorithmic program.

Keywords


Contrast Enhancement, Depth Image, Histogram Modification, Histogram Partitioning.