IEM: A New Image Enhancement Metric for Contrast and Sharpness Measurements

L, Jaya V.; Gopikakumari, R.

doi:10.5120/13766-1620

Cited by 43 publications

(12 citation statements)

References 29 publications

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“…Pada penelitian ini dilakukan IQA menggunakan Mean Squared Error (MSE) dan Peak Signal to Noise Ratio (PSNR) untuk mengukur kinerja metode contrast enhancement dalam menigkatkan kualitas citra [23]. MSE merepresentasikan rata-rata eror kuadrat antara citra masukan dengan citra hasil enhancement.…”

Section: Image Quality Assessment (Iqa)unclassified

Peningkatan Kualitas Citra Malaria Menggunakan Metode Contrast Enhancement Berbasis Histogram

Setyawan

Wuryandari²,

Wibowo³

2022

JIKO

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Akusisi citra digital malaria dapat menghasilkan citra dengan kontras rendah. Hal ini dapat disebabkan karena pengaturan pencahayaan pada mikroskop yang rendah dan penyesuaian parameter pada image capturing software yang tidak tepat. Citra malaria dengan kontras rendah dapat menjadikan segmentasi eritrosit dan plasmodium dari background menjadi tidak akurat. Segmentasi yang tidak akurat juga berdampak terhadap proses ekstraksi fitur dan klasifikasi pada sistem diagnosis malaria otomatis. Oleh karena itu, diperlukan contrast enhancement pada tahap pra pemrosesan untuk menghasilkan citra dengan kualitas yang baik. Pada penelitian ini, kinerja metode contrast enhancement berbasis histogram, yaitu Histogram Equalization (HE), Adapative Histogram Equalization (AHE), dan Contrast Limited Adaptive Histogram Equalization (CLAHE) diuji pada citra malaria untuk mengetahui metode yang menghasilkan citra dengan kualitas terbaik. Hasil pengujian pada dataset MP-IBD, metode CLAHE memberikan hasil yang terbaik dengan nilai MSE 482,35 dan PSNR 21,62. Perbaikan kontras menggunakan CLAHE dapat menghasilkan citra dengan visual eritrosit dan plasmodium yang lebih jelas dan noise yang minimal.

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Section: Image Quality Assessment (Iqa)unclassified

Peningkatan Kualitas Citra Malaria Menggunakan Metode Contrast Enhancement Berbasis Histogram

Setyawan

Wuryandari²,

Wibowo³

2022

JIKO

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“…EMEE 76 is used to calculate an apparent brightness score that follows Weber-Fechner Law with entropy. It is expressed as:…”

Section: No Reference Image Metricmentioning

confidence: 99%

Restoration and enhancement of breast ultrasound images using extended complex diffusion based unsharp masking

Kumar

Srivastava

2021

Proc Inst Mech Eng H

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Ultrasound is a well-known imaging modality for the interpretation of breast cancer. It is playing very important role for breast cancer detection that are missed by mammograms. The image acquisition is usually affected by the presence of noise, artifacts, and distortion. To overcome such type of issues, there is a need of image restoration and enhancement to improve the quality of image. This paper proposes a single framework for denoising and enhancement of ultrasound images, where a smoothing filter is replaced with an extended complex diffusion-based filter in an unsharp masking technique. The performance evaluation of the proposed method is tested on real ultrasound breast cancer images database and synthetic ultrasound image. The performance evaluation comprises qualitative and quantitative evaluation along with comparative analysis of pre-existing and proposed method. The quantitative evaluation metrics are mean squared error, peak-signal-to-noise ratio, correlation parameter, normalized absolute error, universal quality index, similarity structure index, edge preservation index, a measure of enhancement, a measure of enhancement by entropy, and second derivative like measurement. The result specifies that the proposed method is better suited approach for the removal of speckle noise which follows Rayleigh distribution, restoration of information, enhancement of abnormalities, and proper edge preservation.

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“…The conventional measures actually calculate the difference between two images and therefore it can be used for both restoration and enhancement. These measures are taken from [5]. …”

Section: Conventional Measures Of Contrastmentioning

confidence: 99%

“…Contrast based measures of enhancement methods, especially in spatial domain, use the intensities of pixels for calculation purpose. These spatial contrast measures are usually derived from Weber-Fechner law, Michelson contrast measure [5], or Contrast Ratio (CR). The measures PSNR, EME, AMEE [6], SOE, EC, and so forth are examples of such spatial contrast measures [7, 8].…”

Section: Introductionmentioning

confidence: 99%

Appropriate Contrast Enhancement Measures for Brain and Breast Cancer Images

Gupta

Porwal

2016

International Journal of Biomedical Imaging

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Medical imaging systems often produce images that require enhancement, such as improving the image contrast as they are poor in contrast. Therefore, they must be enhanced before they are examined by medical professionals. This is necessary for proper diagnosis and subsequent treatment. We do have various enhancement algorithms which enhance the medical images to different extents. We also have various quantitative metrics or measures which evaluate the quality of an image. This paper suggests the most appropriate measures for two of the medical images, namely, brain cancer images and breast cancer images.

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IEM: A New Image Enhancement Metric for Contrast and Sharpness Measurements

Cited by 43 publications

References 29 publications

Peningkatan Kualitas Citra Malaria Menggunakan Metode Contrast Enhancement Berbasis Histogram

Peningkatan Kualitas Citra Malaria Menggunakan Metode Contrast Enhancement Berbasis Histogram

Restoration and enhancement of breast ultrasound images using extended complex diffusion based unsharp masking

Appropriate Contrast Enhancement Measures for Brain and Breast Cancer Images

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