Contrast and Colour Improvement based Haze Removal of Satellite Images using Fusion Technique
Objective
Our proposed underwater image enhancement technique employs fusion, contrast stretching, and Auto White Balance to mitigate light scattering and absorption effects, improving color, contrast, and object visibility in degraded underwater images.
Abstract
This research focuses on advancing the quality of satellite images by proposing a novel Haze Removal technique based on Contrast and Colour Improvement through Fusion. The method employs a sophisticated Fusion Technique, integrating key components such as weight maps derived from chromatic maps and saliency maps of Contrast and White Images. By harnessing the synergies between these elements, the proposed approach enhances image contrast and improves color representation, particularly in the presence of haze in satellite imagery. The use of weight maps facilitates selective emphasis on important features, ensuring a targeted and effective enhancement process. This method addresses the challenges associated with haze distortion in satellite images, offering a comprehensive solution for image quality improvement. The keywords, including Fusion, Image Enhancement, Haze Satellite Image, and Weight Maps, succinctly capture the essential aspects of this innovative approach to satellite image processing.
Keywords: Fusion, Image Enhancement, Haze Satellite Image, Weight map
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 2020a 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
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, not projects of or by IEEE.
