Proceedings ArticleDOI
Histogram based contrast enhancement for mammogram images
M. Sundaram,K. Ramar,Natarajan Arumugam,G. Prabin +3 more
- pp 842-846
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TLDR
The Histogram Modified Contrast Limited Adaptive Histogram Equalization (HM-CLAHE) is proposed in this paper to adjust the level of contrast enhancement, which in turn gives the resultant image a strong contrast and brings the local details for more relevant interpretation.Abstract:
Early detection of breast cancer in the mammograms is very essential in the field of medicine. Contrast enhancement for the detection of micro calcification of mammograms based on the Histogram Modified Contrast Limited Adaptive Histogram Equalization (HM-CLAHE) is presented. Histogram equalization is an effective and simple technique for contrast enhancement. The standard histogram equalization (HE) usually results in excessive contrast enhancement because of lack of control on the level of enhancement. The Histogram Modified Contrast Limited Adaptive Histogram Equalization (HM-CLAHE) is proposed in this paper to adjust the level of contrast enhancement, which in turn gives the resultant image a strong contrast and brings the local details for more relevant interpretation. It incorporates both histogram modifications as an optimization technique and Contrast Limited Adaptive Histogram Equalization. This method is tested for Mias mammogram images. The performance of this method is determined using the parameter like Enhancement Measure (EME). From the subjective and quantitative measures it is interesting that this proposed technique provides better contrast enhancement with preserving the local information of the mammogram images.read more
Citations
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Journal ArticleDOI
Visibility improvement and mass segmentation of mammogram images using quantile separated histogram equalisation with local contrast enhancement
TL;DR: A working software-based approach named ‘linearly quantile separated histogram equalisation-grey relational analysis’ for mammogram image (MI) improves overall contrast and segments breast-region with a specific end goal to acquire better visual elucidation, examination, and grouping of mammogram masses to help radiologists in settling on more precise choices.
Journal ArticleDOI
Fuzzy C-means and region growing based classification of tumor from mammograms using hybrid texture feature
TL;DR: In the proposed CAD system, pre-processing is performed to suppress the noise in the mammographic image, then segmentation locates the tumor in mammograms using the cascading of Fuzzy C-Means and region-growing algorithm called FCMRG.
Book ChapterDOI
Modified Contrast Limited Adaptive Histogram Equalization Based on Local Contrast Enhancement for Mammogram Images
Shelda Mohan,M. Ravishankar +1 more
TL;DR: The experimental results of proposed LCM-CLAHE method show that this method provides better contrast enhancement with preserving all the local information of the mammogram images.
Journal ArticleDOI
Mammographic Image Enhancement Using Indirect Contrast Enhancement Techniques – A Comparative Study☆
TL;DR: Few indirect contrast enhancement techniques namely histogram equalization, CLAHE, BBHE, RMSHE, MMBEBHE to preprocess the mammographic images are applied and the performance is measured using effective measure of enhancement (EME) and peak signal to noise ratio (PSNR).
Journal ArticleDOI
Local energy-based shape histogram feature extraction technique for breast cancer diagnosis
TL;DR: It is concluded that LESH features are an excellent choice for extracting significant clinical information from mammogram images with significant potential for application to 3-D MRI images.
References
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Journal ArticleDOI
Adaptive histogram equalization and its variations
Stephen M. Pizer,Stephen M. Pizer,E. Philip Amburn,E. Philip Amburn,John D. Austin,Robert Cromartie,Ari Geselowitz,Ari Geselowitz,Trey Greer,Bart M. ter Haar Romeny,John B. Zimmerman,John B. Zimmerman +11 more
TL;DR: It is concluded that clipped ahe should become a method of choice in medical imaging and probably also in other areas of digital imaging, and that clip ahe can be made adequately fast to be routinely applied in the normal display sequence.
Journal ArticleDOI
Adaptive image contrast enhancement using generalizations of histogram equalization
TL;DR: A scheme for adaptive image-contrast enhancement based on a generalization of histogram equalization (HE), which can produce a range of degrees of contrast enhancement, at one extreme leaving the image unchanged, at another yielding full adaptive equalization.
Journal ArticleDOI
Image enhancement via adaptive unsharp masking
TL;DR: A new method for unsharp masking for contrast enhancement of images is presented that employs an adaptive filter that controls the contribution of the sharpening path in such a way that contrast enhancement occurs in high detail areas and little or no image sharpening occurs in smooth areas.
Journal ArticleDOI
Transform-based image enhancement algorithms with performance measure
TL;DR: A new class of the "frequency domain"-based signal/image enhancement algorithms including magnitude reduction, log-magnitude reduction, iterative magnitude and a log-reduction zonal magnitude technique, based on the so-called sequency ordered orthogonal transforms, which include the well-known Fourier, Hartley, cosine, and Hadamard transforms.