Denoising of the Medical Image using Haar SWT in Comparison with Daubechies Wavelet
Objective
The objective of this project is to compare the performance of Haar and Daubechies wavelet transforms in denoising medical images.
Abstract
Noise is an important factor that degrades the quality of medical images. Impulse noise is a common noise caused by malfunctioning of sensor elements or errors in the transmission of images. In medical images due to presence of white foreground and black background, many pixels have intensities similar to impulse noise and hence the distinction between noisy and regular pixels is difficult. Therefore, it is important to design a method to accurately remove this type of noise. In addition to the accuracy, the complexity of the method is very important in terms of hardware implementation. In this paper a low complexity de-noising method is proposed that distinguishes between noisy and non-noisy pixels and removes the noise by local analysis of the image blocks.
Keywords: Impulse Noise, image processing techniques, Filtering Techniques, MATLAB.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2018a or above
Hardware:
Operating Systems:
· Windows 10
· Windows 7 Service Pack 1
· Windows Server 2019
· Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is an Image/pixel?
· About image formats
· Introduction to Image Processing
· How digital image is formed
· Importing the image via image acquisition tools
· Analyzing and manipulation of image.
· Phases of image processing:
o Acquisition
o Image enhancement
o Image restoration
o Color image processing
o Image compression
o Morphological processing
o Segmentation etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Related Projects
Paper Publishing
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Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
