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Ramp Distribution-Based Contrast Enhancement Techniques and Over-Contrast Measure
- Source :
- IEEE Access, Vol 7, Pp 73004-73019 (2019)
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2019.
-
Abstract
- Our approach to contrast enhancement (CE) of images is based on natural scene statistics (NSS). We show, in this paper, that the average intensity distribution of natural images can be linearly approximated to the ramp distribution in an ordered histogram domain as the contrast increases. Based on this finding, we propose ramp distribution-based global and local CE algorithms. The ramp distribution-based slant thresholding (RDST) algorithm is proposed as a global CE method which uses slant thresholding in an ordered histogram domain to yield a contrast-enhanced image. Also, the ramp distribution-based adaptive slant thresholding (RDAST) algorithm is proposed as a local CE method. It adaptively adjusts a slant angle of the ramp distribution in each block to suppress noise amplification in uniform regions and maximizes contrast in non-uniform regions. The RDAST also employs a scaled global modified histogram to minimize sensitivity to block size changes. Moreover, we propose a metric to measure the amount of over-contrast in an image to evaluate all CE algorithms more correctly. The experimental results show that the proposed algorithms have better or competitive performance as well as computational efficiency.
- Subjects :
- General Computer Science
Computer science
media_common.quotation_subject
General Engineering
Thresholding
Noise
Computer Science::Computer Vision and Pattern Recognition
Histogram
Image enhancement
Metric (mathematics)
contrast enhancement
Contrast (vision)
General Materials Science
Adaptive histogram equalization
over-contrast measure
lcsh:Electrical engineering. Electronics. Nuclear engineering
Sensitivity (control systems)
lcsh:TK1-9971
Block size
Algorithm
ramp distribution
media_common
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 7
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....43ad71fc920514ca400c3752823b3a44