Contrast enhancement dynamic histogram equalization for medical image processing application

Ismail, Wan Abdul Fattah Wan; Sim, K. S.

doi:10.1002/ima.20295

Cited by 32 publications

(23 citation statements)

References 12 publications

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“…Histogram equalization is a contrast stretching technique that is widely used in medical image pre-processing [17,20]. Higher histogram equalization is accomplished when there is an effective spreading out of the most frequent intensity values as derived from Eq.…”

Section: Contrast Stretching Method: Histogram Equalizationmentioning

confidence: 99%

“…Conventional histogram equalization, or contrast stretching, has also been investigated as an enhancement technique frequently applied in medical image processing. This is due to its capability of highly enhancing the contrast of blurred images for better target detection and segmentation [17]. Recently, some new improvement techniques on histogram equalization have been proposed [18].…”

Section: Introductionmentioning

confidence: 99%

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Comparative Evaluation of Medical Thermal Image Enhancement Techniques for Breast Cancer Detection

Wahab

Salim

Yunus

et al. 2018

J. Eng. Technol. Sci.

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Thermography is a potential medical imaging modality due to its capability in providing additional physiological information. Medical thermal images obtained from infrared thermography systems incorporate valuable temperature properties and profiles, which could indicate underlying abnormalities. The quality of thermal images is often degraded due to noise, which affects the measurement processes in medical imaging. Contrast stretching and image filtering techniques are normally adopted in medical image enhancement processes. In this study, a comparative evaluation of contrast stretching and image filtering on individual channels of true color thermal images was conducted. Their individual performances were quantitatively measured using mean square error (MSE) and peak signal to noise ratio (PSNR). The results obtained showed that contrast stretching altered the temperature profile of the original image while image filtering appeared to enhance the original image with no changes in its profile. Further measurement of both MSE and PSNR showed that the Wiener filtering method outperformed other filters with an average MSE value of 0.0045 and PSNR value of 78.739 dB. Various segmentation methods applied to both filtered and contrast stretched images proved that the filtering method is preferable for in-depth analysis.

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Section: Contrast Stretching Method: Histogram Equalizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparative Evaluation of Medical Thermal Image Enhancement Techniques for Breast Cancer Detection

Wahab

Salim

Yunus

et al. 2018

J. Eng. Technol. Sci.

View full text Add to dashboard Cite

show abstract

“…The idea of contrast stretching is to increase the dynamic range of intensity level in the processed image. The functioning of the contrast stretching operation on gray scale image is to apply the following equation on each of the pixels in the input image to form the corresponding output image pixel by Ismail and Sim (2011).…”

Section: Image Enhancement Model (Contrast Stretching)mentioning

confidence: 99%

An Enhanced Approach for Medical Brain Image Enhancement

V.¹

2012

Journal of Computer Science

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Problem statement: One of the most common degradations in medical images is their poor contrast quality and noise. The DICOM image consists of speckle (multiplicative noise). While the image is enhanced, the multiplicative noise present in the image is also enhanced. Approach: This study describes the hybrid method to improve the image quality of Digital Imaging and Communications in Medicine (DICOM) images. The idea of image enhancement technique is to improve the quality of an image for early diagnosis. Then followed by a noise reduction using speckle reduction anisotropic filter. This suggests the use of contrast enhancement methods as an attempt to modify the intensity distribution of the image and to reduce the multiplicative noise. Results: In this research study, a new approach for DICOM image is done by applying contrast stretching and anisotropic diffusion where denoising of multiplicative noise is carried out and the level of contrast is improved. The quality of the image is enhanced and noise free for DICOM image analysis. The effectiveness of hybrid method is proved by quantitative approach. Conclusion and Recommendation: The performance of the proposed study is compared with the existing traditional algorithm and real time medical diagnosis image.

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“…In another example, Sim et al 6 has applied contrast enhancement to protrude pertinent magnetic resonance (MR) brain image features because the MR brain images were obscured by dark background and therefore, showing hard-to-perceive structural delineation. As contrast enhancement for medical image needs to consider excellent output visual quality and minimization of undesirable side effects such as washed-out effect and image artifact, Sim (CEDHE).…”

Section: Introductionmentioning

confidence: 98%

Medical Image Contrast Enhancement Using Spline Concept: Data from the Osteoarthritis Initiative

Gan¹,

Swee²,

Kadir³

et al. 2014

J Med Imaging Hlth Inform

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Excellent visual quality of medical image is important for subsequent image interpretation and diagnosis planning. Hence, preservation of brightness and considerable tissue contrast improvement are essential for this purpose. Previous histogram equalization methods tend to focus on brightness preservation and neglect the need to address excessive contrast enhancement. However, gray level medical images are highly sensitive to redundant adjustment of image contrast. In this work, we propose to implement cubic spline to reduce the difference in pixel intensity prior to histogram equalization while retaining the partition of histogram to prevent dramatic mean brightness shift in resultant image. Qualitative results indicate that our proposed contrast enhancement method is capable of avoiding extreme brightness elevation and excessive tissue contrast improvement to provide holistic views of the knee MR images. In future, we would like to recommend the development of adaptive data interval to substitute the uniform data point intervals.

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Contrast enhancement dynamic histogram equalization for medical image processing application

Cited by 32 publications

References 12 publications

Comparative Evaluation of Medical Thermal Image Enhancement Techniques for Breast Cancer Detection

Comparative Evaluation of Medical Thermal Image Enhancement Techniques for Breast Cancer Detection

An Enhanced Approach for Medical Brain Image Enhancement

Medical Image Contrast Enhancement Using Spline Concept: Data from the Osteoarthritis Initiative

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