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Book ChapterDOI

Combination of Wavelet Transform and Morphological Filtering for Enhancement of Magnetic Resonance Images

TLDR
An improved framework for enhancement of cerebral MRI features by incorporating enhancement approaches of both the frequency and spatial domain is presented and a good enhancement of Region Of Interest (ROI) is obtained.
Abstract
Brain tumor is an abnormal mass of tissue with uncoordinated growth inside the skull which may invade and damage nerves and other healthy tissues. Limitations posed by the image acquisition systems leads to the inaccurate analysis of magnetic resonance images (MRI) even by the skilled neurologists. This paper presents an improved framework for enhancement of cerebral MRI features by incorporating enhancement approaches of both the frequency and spatial domain. The proposed method requires de-noising, enhancement using a non-linear enhancement function in wavelet domain and then iterative enhancement algorithm using the morphological filter for further enhancing the edges is applied. A good enhancement of Region Of Interest(ROI) is obtained with the proposed method which is well portrayed by estimates of three quality metrics. Contrast improvement index (CII), peak signal to noise ratio (PSNR) and average signal to noise ratio (ASNR).

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Citations
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Journal ArticleDOI

Segmentation of Ischemic Stroke Lesion in Brain MRI Based on Social Group Optimization and Fuzzy-Tsallis Entropy

TL;DR: A hybrid semi-automated image processing methodology is proposed to inspect the ischemic stroke lesion using the MRI recorded with flair and diffusion-weighted modality to estimate the stroke severity and also to plan for further treatment process.
Proceedings ArticleDOI

Medical image fusion with Laplacian Pyramids

TL;DR: The proposed technique provides a fused image with better edges and information content from human visual system (HVS) point of view and is found to be superior than that of Daubechies complex wavelet transform (DCxWT).
Proceedings ArticleDOI

Medical image fusion using combination of PCA and wavelet analysis

TL;DR: Medical image fusion for merging of complementary diagnostic content has been carried out using Principal Component Analysis (PCA) and Wavelets and results demonstrate an improvement in visual quality of the fused image in comparison to other state-of-art fusion approaches.
Journal ArticleDOI

Speckle suppression in SAR images employing modified anisotropic diffusion filtering in wavelet domain for environment monitoring

TL;DR: Based on the simulation results as well as the values of image quality metrics; filtered SAR images obtained by the proposed speckle suppression methodology can be claimed better in comparison to other recent works.
Book ChapterDOI

A Composite Wavelets and Morphology Approach for ECG Noise Filtering

TL;DR: A combination of wavelets analysis and morphological filtering as an approach for noise removal in ECG signals using bi-orthogonal wavelet family is presented.
References
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Book

A wavelet tour of signal processing

TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
Book

Ten lectures on wavelets

TL;DR: This paper presents a meta-analyses of the wavelet transforms of Coxeter’s inequality and its applications to multiresolutional analysis and orthonormal bases.
Journal ArticleDOI

Ten Lectures on Wavelets

TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.
Journal ArticleDOI

Contrast limited adaptive histogram equalization image processing to improve the detection of simulated spiculations in dense mammograms.

TL;DR: The selected CLAHE settings should be tested in the clinic with digital mammograms to determine whether detection of spiculations associated with masses detected at mammography can be improved.
Journal ArticleDOI

An advanced contrast enhancement using partially overlapped sub-block histogram equalization

TL;DR: In this paper, a low-pass filter-type mask is used to get a nonoverlapped sub-block histogram-equalization function to produce the high contrast associated with local histogram equalization but with the simplicity of global histogram equivalence.
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