Medical X-Ray Image Enhancement Based on Wavelet Domain Homomorphic Filtering and CLAHE

He, Wen; Wu, Qi; Li, Shuang

doi:10.1109/icris.2016.50

Cited by 25 publications

(14 citation statements)

References 8 publications

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“…The log-transformed residual image is then filtered with an HMF-H(x, y) for correcting the non-uniform illumination of the CXR [29,30]. We stress one more time that the HMF is used to reduce inhomogeneous effects of CXRs.…”

Section: Homomorphic Filtering-hmfmentioning

confidence: 99%

“…Finally, the calculation of the new gray-level assignment of the pixels is achieved within a sub-matrix contextual region by using a bi-linear interpolation between four different mappings to eliminate boundary artifacts. CLAHE was already applied for the enhancement of contrast in medical images [30,[41][42][43]. Huang proposed CLAHE-DWT (DWT is for discrete wavelet transform) using a combination of CLAHE and DWT to overcome the limitations of CLAHE which faces the contrast overstretching and noise enhancement problems.…”

Section: Contrast Limited Adaptive Histogram Equalization-clahementioning

confidence: 99%

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Pipeline for Advanced Contrast Enhancement (PACE) of Chest X-ray in Evaluating COVID-19 Patients by Combining Bidimensional Empirical Mode Decomposition and Contrast Limited Adaptive Histogram Equalization (CLAHE)

et al. 2020

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COVID-19 is a new pulmonary disease which is driving stress to the hospitals due to the large number of cases worldwide. Imaging of lungs can play a key role in the monitoring of health status. Non-contrast chest computed tomography (CT) has been used for this purpose, mainly in China, with significant success. However, this approach cannot be massively used, mainly for both high risk and cost, also in some countries, this tool is not extensively available. Alternatively, chest X-ray, although less sensitive than CT-scan, can provide important information about the evolution of pulmonary involvement during the disease; this aspect is very important to verify the response of a patient to treatments. Here, we show how to improve the sensitivity of chest X-ray via a nonlinear post-processing tool, named PACE (Pipeline for Advanced Contrast Enhancement), combining properly Fast and Adaptive Bidimensional Empirical Mode Decomposition (FABEMD) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The results show an enhancement of the image contrast as confirmed by three widely used metrics: (i) contrast improvement index, (ii) entropy, and (iii) measure of enhancement. This improvement gives rise to a detectability of more lung lesions as identified by two radiologists, who evaluated the images separately, and confirmed by CT-scans. The results show this method is a flexible and an effective approach for medical image enhancement and can be used as a post-processing tool for medical image understanding and analysis.

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Section: Homomorphic Filtering-hmfmentioning

confidence: 99%

Section: Contrast Limited Adaptive Histogram Equalization-clahementioning

confidence: 99%

Pipeline for Advanced Contrast Enhancement (PACE) of Chest X-ray in Evaluating COVID-19 Patients by Combining Bidimensional Empirical Mode Decomposition and Contrast Limited Adaptive Histogram Equalization (CLAHE)

et al. 2020

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“…The picture is divided by DWT; the picture is disintegrated into low-frequency and high-frequency coefficients of first layer of wavelet space. At that point the low frequency coefficients are prepared by an enhanced homomorphic channel, and after that direct increased [8].…”

Section: Literature Reviewmentioning

confidence: 99%

A Comparative Analysis on Histogram Equalization Techniques for Medical Image Enhancement

Singh¹,

Singh²

2017

IJARCSSE

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Image enhancement (IE) is such technique which makes the processing on image in order to increase its effectiveness for computer to process. Enhancement is, used for improvement of the visual effects and the clarity of image.Medical image is used as the important information and basis for the clinical diagnosis, while its quality digressed because of the interferences caused by the human body structure, equipment's, and environmental factors. In this paper review, the enhancement of medical images using efficient algorithms based on HE techniques. Also evaluate the result of medical image on technique to histogram equalization (HE), adaptive histogram equalization (AHE), (BBHE) and contrast limited adaptive histogram equalization (CLAHE) to compare the pre-processing of image.

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“…Its purpose is to highlight certain image features for analysis, diagnosis, characterization and decision making. Histogram and Gradient analysis plays a crucial role in image processing applications for the purpose of better image visualization and details enhancements in order to achieve objectives such as segmentation and edge detection (Suganya et al, 2013;Zhou and Yicong, 2016;He Wen and Li, 2016;Cheolkon and Yang, 2016;Qiong et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Characterization of Composite Structure Surface Uniformity using Interval Based Gradient Field Histogram Analysis of Thermographic Images (IGF-HA)

Iskandarani¹

2018

Journal of Computer Science

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This paper presents a new approach to composite surface characterization using Image Histogram Analysis as a function of Gradient Field. Image sequences are weighed and combined in order to present a pattern change in the thermal response of a tested composite structure. Reaction Injection Molding samples used and subjected to thermal energy to characterize their surface uniformity and any existing damage. A threshold value is used for the purpose of segmenting and separating damaged from undamaged areas in the tested composite structure. Gradient field analysis established the critical time at which the surface started to show damage and segmented the tested images into areas of concern. The resulting histograms cover four main regions of interest according to the gradient intensities as a function of time. Each region is divided into eight subsections according to the corresponding limit value, resulting in thirty two subsections. Correlation between region gradient field and its histogram resulted in uncovering of surface deformities as a function of surface area thermal storage. The process is modeled mathematically.

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Medical X-Ray Image Enhancement Based on Wavelet Domain Homomorphic Filtering and CLAHE

Cited by 25 publications

References 8 publications

Pipeline for Advanced Contrast Enhancement (PACE) of Chest X-ray in Evaluating COVID-19 Patients by Combining Bidimensional Empirical Mode Decomposition and Contrast Limited Adaptive Histogram Equalization (CLAHE)

Pipeline for Advanced Contrast Enhancement (PACE) of Chest X-ray in Evaluating COVID-19 Patients by Combining Bidimensional Empirical Mode Decomposition and Contrast Limited Adaptive Histogram Equalization (CLAHE)

A Comparative Analysis on Histogram Equalization Techniques for Medical Image Enhancement

Characterization of Composite Structure Surface Uniformity using Interval Based Gradient Field Histogram Analysis of Thermographic Images (IGF-HA)

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