Local and Global Contrast Stretching For Color Contrast Enhancement on Ziehl-Neelsen Tissue Section Slide Images

Sahidan, Shahiana Izma; Mashor, Mohd Yusoff; Wahab, A.S.W.; Salleh, Z.; Jaafar, Hasnan

doi:10.1007/978-3-540-69139-6_146

Cited by 15 publications

(11 citation statements)

References 11 publications

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“…To increase the contrast of the image, the global contrast stretching (GCS) technique which can spread out the range of scene illumination is employed. GCS is performed by sliding a window (called the KERNEL) across the image and adjusting the center element using the following formula [ 25 ]:

where ( x , y ) is the coordinate of the image pixel; I p ( x , y ) is the output color level for the pixel ( x , y ) from the contrast stretching process; I o ( x , y ) is the input color level for the pixel ( x , y ); min and max are the minimum and maximum color level value in the input image.…”

Section: Methodsmentioning

confidence: 99%

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Segmentation of White Blood Cell from Acute Lymphoblastic Leukemia Images Using Dual-Threshold Method

Zhu

Lei

et al. 2016

Computational and Mathematical Methods in Medicine

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We propose a dual-threshold method based on a strategic combination of RGB and HSV color space for white blood cell (WBC) segmentation. The proposed method consists of three main parts: preprocessing, threshold segmentation, and postprocessing. In the preprocessing part, we get two images for further processing: one contrast-stretched gray image and one H component image from transformed HSV color space. In the threshold segmentation part, a dual-threshold method is proposed for improving the conventional single-threshold approaches and a golden section search method is used for determining the optimal thresholds. For the postprocessing part, mathematical morphology and median filtering are utilized to denoise and remove incomplete WBCs. The proposed method was tested in segmenting the lymphoblasts on a public Acute Lymphoblastic Leukemia (ALL) image dataset. The results show that the performance of the proposed method is better than single-threshold approach independently performed in RGB and HSV color space and the overall single WBC segmentation accuracy reaches 97.85%, showing a good prospect in subsequent lymphoblast classification and ALL diagnosis.

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Section: Methodsmentioning

confidence: 99%

“…Some work on microscopic WBC image segmentation is available in the literature [ 3 – 25 ]. Methods can be classified into three types: threshold-based methods, pattern recognition-based methods, and deformable model-based methods.…”

Section: Introductionmentioning

confidence: 99%

Segmentation of White Blood Cell from Acute Lymphoblastic Leukemia Images Using Dual-Threshold Method

Zhu

Lei

et al. 2016

Computational and Mathematical Methods in Medicine

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“…The formula for global contrast stretching is governed by the following equation [19]:

\begin{matrix} {out}_{RGB} (x, y) = 255 * [\frac{({in}_{RGB} (x, y) - \min_{RGB})}{\max_{RGB} - \min_{RGB}}], \end{matrix}

where in RGB ( x , y ) is The original RGB value of the pixel, out RGB ( x , y ) is the new RGB value of the pixel, min⁡ RGB is minimum value between the RGB components, and max⁡ RGB is maximum value between the RGB components…”

Section: Methodsmentioning

confidence: 99%

Modified Global and Modified Linear Contrast Stretching Algorithms: New Colour Contrast Enhancement Techniques for Microscopic Analysis of Malaria Slide Images

Nasir

Mashor

Mohamed

2012

Computational and Mathematical Methods in Medicine

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Malaria is one of the serious global health problem, causing widespread sufferings and deaths in various parts of the world. With the large number of cases diagnosed over the year, early detection and accurate diagnosis which facilitates prompt treatment is an essential requirement to control malaria. For centuries now, manual microscopic examination of blood slide remains the gold standard for malaria diagnosis. However, low contrast of the malaria and variable smears quality are some factors that may influence the accuracy of interpretation by microbiologists. In order to reduce this problem, this paper aims to investigate the performance of the proposed contrast enhancement techniques namely, modified global and modified linear contrast stretching as well as the conventional global and linear contrast stretching that have been applied on malaria images of P. vivax species. The results show that the proposed modified global and modified linear contrast stretching techniques have successfully increased the contrast of the parasites and the infected red blood cells compared to the conventional global and linear contrast stretching. Hence, the resultant images would become useful to microbiologists for identification of various stages and species of malaria.

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“…The second most widely used contrast modification approach is global contrast stretching (GCS). This technique enhances the image from the luminance information of all of the pixels and is governed by the equation:

j = 255 \times \frac{i - i_{m i n}}{i_{m a x} - i_{m i n}}

…”

Section: Mammogram Contrast Enhancement Techniquesmentioning

confidence: 99%

Automatic intensity windowing of mammographic images based on a perceptual metric

2017

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Purpose: Initial auto-adjustment of the window level WL and width WW applied to mammographic images. The proposed intensity windowing (IW) method is based on the maximization of the mutual information (MI) between a perceptual decomposition of the original 12-bit sources and their screen displayed 8-bit version. Besides zoom, color inversion and panning operations, IW is the most commonly performed task in daily screening and has a direct impact on diagnosis and the time involved in the process. Methods: The authors present a human visual system and perception-based algorithm named GRAIL (Gabor-relying adjustment of image levels). GRAIL initially measures a mammogram's quality based on the MI between the original instance and its Gabor-filtered derivations. From this point on, the algorithm performs an automatic intensity windowing process that outputs the WL/WW that best displays each mammogram for screening. GRAIL starts with the default, high contrast, wide dynamic range 12-bit data, and then maximizes the graphical information presented in ordinary 8-bit displays. Tests have been carried out with several mammogram databases. They comprise correlations and an ANOVA analysis with the manual IW levels established by a group of radiologists. A complete MATLAB implementation of GRAIL is available at https://github.com/TheAnswerIsFortyTwo/GRAIL. Results: Auto-leveled images show superior quality both perceptually and objectively compared to their full intensity range and compared to the application of other common methods like global contrast stretching (GCS). The correlations between the human determined intensity values and the ones estimated by our method surpass that of GCS. The ANOVA analysis with the upper intensity thresholds also reveals a similar outcome. GRAIL has also proven to specially perform better with images that contain micro-calcifications and/or foreign X-ray-opaque elements and with healthy BI-RADS A-type mammograms. It can also speed up the initial screening time by a mean of 4.5 s per image. Conclusions: A novel methodology is introduced that enables a quality-driven balancing of the WL/ WW of mammographic images. This correction seeks the representation that maximizes the amount of graphical information contained in each image. The presented technique can contribute to the diagnosis and the overall efficiency of the breast screening session by suggesting, at the beginning, an optimal and customized windowing setting for each mammogram.

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Local and Global Contrast Stretching For Color Contrast Enhancement on Ziehl-Neelsen Tissue Section Slide Images

Cited by 15 publications

References 11 publications

Segmentation of White Blood Cell from Acute Lymphoblastic Leukemia Images Using Dual-Threshold Method

Segmentation of White Blood Cell from Acute Lymphoblastic Leukemia Images Using Dual-Threshold Method

Modified Global and Modified Linear Contrast Stretching Algorithms: New Colour Contrast Enhancement Techniques for Microscopic Analysis of Malaria Slide Images

Automatic intensity windowing of mammographic images based on a perceptual metric

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