A real-time contrast enhancement algorithm for infrared images based on plateau histogram

Wang, Bingjian; Shang-qian, Liu; Li, Qing; Zhou, Huixin

doi:10.1016/j.infrared.2005.04.008

Cited by 97 publications

(36 citation statements)

References 5 publications

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“…The second step is histogram equalization to get clearer image ( Wang et al, 2006 ) . Histogram equalization is a useful and common method for efficiently enhancing the characteristics of some brighter or darker imagery.…”

Section: Methodsmentioning

confidence: 99%

Coastline Change Assessment at the Aegean Sea Coasts in Turkey Using Multitemporal Landsat Imagery

Ekercin

2007

Journal of Coastal Research

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Section: Methodsmentioning

confidence: 99%

Coastline Change Assessment at the Aegean Sea Coasts in Turkey Using Multitemporal Landsat Imagery

Ekercin

2007

Journal of Coastal Research

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“…In 2006, Wang et al, [36] proposed Self-Adaptive Plateau Histogram Equalization (SAPHE) to enhance the main objects and suppress the background for infrared images. In SAPHE, histogram of the image is filtered with median filter to reduce the fluctuation and also to remove some empty bins inside the histogram and find the local maximum value and global maximum value of histogram for plateau threshold value.…”

Section: Figure 4 Clipped Histogram Equalization(che) Methods (A) Thmentioning

confidence: 99%

A Comparative Analysis of Histogram Equalization based Techniques for Contrast Enhancement and Brightness Preserving

Raju¹,

S²,

Reddy³

2013

IJSIP

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“…Yet, the thresholds in PHE and DPHE need to be manually selected, which limits their usage in practice. As a result, adaptive plateau histogram equalization (APHE) [18], as well as adaptive double plateau histogram equalization (ADPHE) [17], were then developed. However, the robustness of ADPHE cannot be guaranteed because the thresholds are fixed for all the grayscales.…”

Section: Introductionmentioning

confidence: 99%

Infrared Image Enhancement Using Adaptive Histogram Partition and Brightness Correction

Wan

Qian

et al. 2018

Remote Sensing

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Abstract:Infrared image enhancement is a crucial pre-processing technique in intelligent urban surveillance systems for Smart City applications. Existing grayscale mapping-based algorithms always suffer from over-enhancement of the background, noise amplification, and brightness distortion. To cope with these problems, an infrared image enhancement method based on adaptive histogram partition and brightness correction is proposed. First, the grayscale histogram is adaptively segmented into several sub-histograms by a locally weighted scatter plot smoothing algorithm and local minima examination. Then, the fore-and background sub-histograms are distinguished according to a proposed metric called grayscale density. The foreground sub-histograms are equalized using a local contrast weighted distribution for the purpose of enhancing the local details, while the background sub-histograms maintain the corresponding proportions of the whole dynamic range in order to avoid over-enhancement. Meanwhile, a visual correction factor considering the property of human vision is designed to reduce the effect of noise during the procedure of grayscale re-mapping. Lastly, particle swarm optimization is used to correct the mean brightness of the output by virtue of a reference image. Both qualitative and quantitative evaluations implemented on real infrared images demonstrate the superiority of our method when compared with other conventional methods.

show abstract

A real-time contrast enhancement algorithm for infrared images based on plateau histogram

Cited by 97 publications

References 5 publications

Coastline Change Assessment at the Aegean Sea Coasts in Turkey Using Multitemporal Landsat Imagery

Coastline Change Assessment at the Aegean Sea Coasts in Turkey Using Multitemporal Landsat Imagery

A Comparative Analysis of Histogram Equalization based Techniques for Contrast Enhancement and Brightness Preserving

Infrared Image Enhancement Using Adaptive Histogram Partition and Brightness Correction

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