Title
Image Enhancement via Cloud Cascade Control Based Sub-Image-Clipped Histogram Equalization
Abstract
Histogram-Based image enhancement techniques attempts to divide the histogram vertically and horizontally to overcome the saturation effect of intensities and over-enhancement. The proposed cloud-based method makes an effort to modify a classic histogram-based image enhancement by concept of cascade control. Two control loops check the quality of the output image by an inner and outer feedback signals and provide optimal vertical and horizontal separating thresholds to control the sub-image-clipped histogram. Feedback loops include of two genetic algorithm mechanisms as two cloud servers with different image quality metrics as their fitness functions. A controller block is also designed to guarantee the convergence of the algorithms. The experimental results, in a bare metal with GPU cloud instances with mass number of processing cores, show the superiority of the proposed method in comparison with traditional image enhancement schemes.
Year
DOI
Venue
2016
10.1109/SmartCloud.2016.41
2016 IEEE International Conference on Smart Cloud (SmartCloud)
Keywords
Field
DocType
Image Enhancement,Histogram Equalization,Thresholds Clipping,Genetic Algorithm,Image Quality Measurement,Cascade Control,Cloud Environment
Computer vision,Histogram,Control theory,Computer science,Image quality,Histogram matching,Adaptive histogram equalization,Artificial intelligence,Balanced histogram thresholding,Image histogram,Histogram equalization
Conference
ISBN
Citations 
PageRank 
978-1-5090-5264-6
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Paul Rad101.01
Sos S. Agaian274483.01
Mehdi Roopaei300.34
Saeed Sedighi400.34