Weighted average multi segment histogram equalization for brightness preserving contrast enhancement

Khan, Mohd. Farhan; Khan, E.; Abbasi, Z. A.

doi:10.1109/ispcc.2012.6224340

Cited by 22 publications

(11 citation statements)

References 10 publications

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“…Picture handled by Multi-HE routines save the picture brilliance and deflect exordium of undesirable relics yet not altogether improve the differentiation [32].…”

Section: Multi-histogram Equalization Methodsmentioning

confidence: 99%

“…Wadud et al, [32] in 2008, has been exhibited Spatially Controlled Histogram Equalization (SCHE) separating it to different sub-histograms until it discovers that no staggering fragment is shown in any of the from right off the bat made sub-histograms. After that a component powder level (GL) degree is relegated for every one sub-histogram to which its cinder levels can be mapped by histogram equalization.…”

Section: Figure 4 Recursive Mean-separate Histogram Equalization (Rmsmentioning

confidence: 99%

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Histogram Equalization Tool: Brightness Preservation and Contrast Enhancement using Segmentation with Opening-by-Reconstruction

Kaur¹

2015

IJCA

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Sundry improvement plans are used for improving a picture which incorporates ash scale control, sifting and Histogram Equalization (HE). The issue with pictures is that, their quality depends upon a number of different variables like lighting in the picture catching area, commotion and capability of the administrator. The writing addresses the verbalized issue widely and presents answers for them. Contrast improvement systems are used for correcting visual nature of low difference pictures. Histogram Equalization (HE) is one such procedure used for difference upgrade. The proposed illustrations have a few shared traits in their procedures. Approximately every one of them is at fluctuation either in histogram leveling strategies or in picture quality estimation instruments. An instrument is lost in the writing that is proficient to improve the picture and even perform the examination. In this paper, a GUI apparatus is composed which is coupled with different procedures of picture improvement through histogram balance. Opening-byrecreation is a standout amongst the most effective picture division strategy is used to attain to the craved results. To assess the adequacy of the delineated systems; PSNR, Tenengrad, and Absolute Mean Brightness mistake (AMBE) are used as parameters. The results are decently backed by the parameter estimations toward the end. General TermsDigital Image Processing, Image Enhancement and Histogram Equalization.

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“…Picture handled by Multi-HE routines save the picture brilliance and deflect exordium of undesirable relics yet not altogether improve the differentiation [32].…”

Section: Multi-histogram Equalization Methodsmentioning

confidence: 99%

Section: Figure 4 Recursive Mean-separate Histogram Equalization (Rmsmentioning

confidence: 99%

Histogram Equalization Tool: Brightness Preservation and Contrast Enhancement using Segmentation with Opening-by-Reconstruction

Kaur¹

2015

IJCA

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“…In 2012, Khan et al, [34] has proposed Weighted Average Multi Segment Histogram Equalization (WAMSHE), which decomposes smoothed histogram into multiple segments based on optimal thresholds and equalized each segment by histogram equalization. WAMSHE shown better brightness preserving and contrast enhancement among Multi-histogram equalization methods and also helps to reduce the noise present in the image.…”

Section: Multi Histogram Equalization Methodsmentioning

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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“…For the enhancement of low contrast color images a Fast and efficient Fuzzy logic algorithm with histogram equalization is used. In digital image processing Histogram equalization (HE) method is simples [13] most effective technique but it has some limitation that it does not preserve the brightness and original look of images. To overcome this problem several Biand Multi-histogram equalization methods have been proposed.…”

Section: Fuzzy Enhancementmentioning

confidence: 99%

Optimized Adaptive Fuzzy based Image Enhancement Techniques

Kaur¹,

Sidhu²

2016

IJSIP

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Weighted average multi segment histogram equalization for brightness preserving contrast enhancement

Cited by 22 publications

References 10 publications

Histogram Equalization Tool: Brightness Preservation and Contrast Enhancement using Segmentation with Opening-by-Reconstruction

Histogram Equalization Tool: Brightness Preservation and Contrast Enhancement using Segmentation with Opening-by-Reconstruction

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

Optimized Adaptive Fuzzy based Image Enhancement Techniques

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