Human visual system based unsharp masking for enhancement of mammographic images

•NPF has shown distinguished performance when applied for mammogram enhancement.•This paper presents the usage of NPF in design of Non-Linear Unsharp Masking (UM) framework for the enhancement of mammographic images.•Application of HVS based adaptive thresholding and non-linear fusion operators prov...

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Vydáno v:	Journal of computational science Ročník 21; s. 387 - 393
Hlavní autoři:	Bhateja, Vikrant, Misra, Mukul, Urooj, Shabana
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.07.2017
Témata:	Contrast enhancement algorithm Mammograms Non-linear fusion Symmetric logarithmic image processing (SLIP) model Unsharp masking (UM) Non-linear fusion Contrast enhancement algorithm Symmetric logarithmic image processing (SLIP) model Unsharp masking (UM) Mammograms
ISSN:	1877-7503, 1877-7511
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Popis
Shrnutí:	•NPF has shown distinguished performance when applied for mammogram enhancement.•This paper presents the usage of NPF in design of Non-Linear Unsharp Masking (UM) framework for the enhancement of mammographic images.•Application of HVS based adaptive thresholding and non-linear fusion operators provides for an effective minimization of background noises. Non-Linear Polynomial Filters (NPF) consists of a schema of linear and quadratic filter components operating as a fusion of low-and high pass filters. NPF has shown distinguished performance when applied for mammogram enhancement. The role has been multifaceted, as there is visual contrast improvement of Region-of-Interest (ROI), i.e. the tumor region as well as those of the surrounding diagnostic features. This paper presents the usage of NPF in design of Non-Linear Unsharp Masking (UM) framework for the enhancement of X-ray mammograms (digital mammographic images). The UM approach presented consists of operational modules namely: edge preserving and contrast enhancement algorithms which are realized using different variants of NPF. Application of Human Visual System (HVS) based adaptive thresholding during contrast enhancement provides for an effective minimization of background noises. The responses of the different modules are then combined using non-linear fusion operators based on an improved logarithmic model of perception and human vision. The obtained enhancement results demonstrate noteworthy improvement in contrast of lesion region together with better visualization of lesion margins and fine details. It has been subjectively as well as objectively shown that the enhancement of the contrast and edges do not introduces unwanted overshoots in the ROI.
ISSN:	1877-7503 1877-7511
DOI:	10.1016/j.jocs.2016.07.015