Quadrants dynamic histogram equalization for contrast enhancement

Ooi, Chen Hee; Isa, Nor Ashidi Mat

doi:10.1109/tce.2010.5681140

Cited by 133 publications

(51 citation statements)

References 14 publications

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“…A histogram of the image is filtered in SAPHE with median filter to reduce the fluctuation and additionally to abstract some empty bins in the histogram and find the local maximum value and global maximum value of the histogram for plateau threshold value. By eradicating median filter from SAPHE, Nicholas et al, [37] introduced modified SAPHE (MSAPHE) in 2009 to enhance microscopic images. SAPHE failed to identify local peaks in the image and MASAPHE has overcome this issue.…”

Section: Clipped Histogram Equalization Methodsmentioning

confidence: 99%

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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Section: Clipped Histogram Equalization Methodsmentioning

confidence: 99%

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

Kaur¹

2015

IJCA

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“…Ooi et al, [39] in 2010 introduced clipping based Quadrants Dynamic Histogram equalization (QDHE), which separates the histogram into four sub-histograms based on the median of the input image. Then, the resultant sub-histograms are clipped according to the mean of intensity occurrence of the input image before new dynamic range is assigned to each sub-histogram and are equalized individually.…”

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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“…Despite of its popularity, CHE normally introduces undesirable visual artifacts in the processed images due to either excessive brightness shift [2][3], or over enhancement of noisy regions [4][5], or saturation of intensities [6][7]. To overcome these limitations of CHE method, numerous solutions have been suggested in the literature [2][3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…To overcome these limitations of CHE method, numerous solutions have been suggested in the literature [2][3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Semi dynamic fuzzy histogram equalization

Khan

Ren

Khan

2015

Optik

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Quadrants dynamic histogram equalization for contrast enhancement

Cited by 133 publications

References 14 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

Semi dynamic fuzzy histogram equalization

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