Evaluation of Perceptual Contrast and Sharpness Measures for Meteorological Satellite Images

Prajapati, Payal; Narmawala, Zunnun; Darji, Nikunj P.; Moorthi, S. Manthira; Ramakrishnan, R.

doi:10.1016/j.procs.2015.07.358

Cited by 11 publications

(4 citation statements)

References 12 publications

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“…Shannon function (46) where X is the image that we apply the function and µ mn is the degree of participation of the fuzzified image [37,39].…”

Section: Entropymentioning

confidence: 99%

“…Michelson's law measure of enhancement (AME) divides an image into blocks with size m × n and then calculates from the whole image the average values of the measured results. The higher the score, the better the enhancement performance [7,46,47]. The function for AME is:…”

Section: Amementioning

confidence: 99%

“…Michelson's law measure of enhancement by entropy (AMEE) has the same procedure as AME but a different function. The higher the score, the better the enhancement performance [7,9,[46][47][48]. Function of AMEE:…”

Section: Ameementioning

confidence: 99%

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Advanced Fuzzy Sets and Genetic Algorithm Optimizer for Mammographic Image Enhancement

Dounis,

Avramopoulos,

Kallergi

2023

Electronics

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A well-researched field is the development of Computer Aided Diagnosis (CADx) Systems for the benign-malignant classification of abnormalities detected by mammography. Due to the nature of the breast parenchyma, there are significant uncertainties about the shape and geometry of the abnormalities that may lead to an inaccurate diagnosis. These same uncertainties give mammograms a fuzzy character that is essential to the application of fuzzy processing. Fuzzy set theory considers uncertainty in the form of a membership function, and therefore fuzzy sets can process imperfect data if this imperfection originates from vagueness and ambiguity rather than randomness. Fuzzy contrast enhancement can improve edge detection and, by extension, the quality of related classification features. In this paper, classical (Linguistic hedges and fuzzy enhancement functions), advanced fuzzy sets (Intuitionistic fuzzy set (ΙFS), Pythagorean fuzzy set (PFS), and Fermatean fuzzy sets (FFS)), and a Genetic Algorithm optimizer are proposed to enhance the contrast of mammographic features. The advanced fuzzy sets provide better information on the uncertainty of the membership function. As a result, the intuitionistic method had the best overall performance, but most of the techniques could be used efficiently, depending on the problem that needed to be solved. Linguistic methods could provide a more manageable way of spreading the histogram, revealing more extreme values than the conventional methods. A fusion technique of the enhanced mammography images with Ordered Weighted Average operators (OWA) achieves a good-quality final image.

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“…Shannon function (46) where X is the image that we apply the function and µ mn is the degree of participation of the fuzzified image [37,39].…”

Section: Entropymentioning

confidence: 99%

Section: Amementioning

confidence: 99%

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Advanced Fuzzy Sets and Genetic Algorithm Optimizer for Mammographic Image Enhancement

Dounis,

Avramopoulos,

Kallergi

2023

Electronics

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“…(i) Measure of enhancement (EME) EME 75 provides an absolute score of every image that are based on the image contrast which follows Fechner's Law of contrast. The respective formula of EME is stated 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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Analysis of Blood Smear Images Using Dark Contrast Algorithm and Morphological Filters

Gupta

Bhateja

Verma

et al. 2023

Smart Innovation, Systems and Technologies

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Evaluation of Perceptual Contrast and Sharpness Measures for Meteorological Satellite Images

Cited by 11 publications

References 12 publications

Advanced Fuzzy Sets and Genetic Algorithm Optimizer for Mammographic Image Enhancement

Advanced Fuzzy Sets and Genetic Algorithm Optimizer for Mammographic Image Enhancement

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

Analysis of Blood Smear Images Using Dark Contrast Algorithm and Morphological Filters

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