Fourier Mellin Transform-based Image Registration System and Alignment in MATLAB

Problem Definition

The field of image registration presents various challenges and limitations that hinder its efficiency across different domains, including remote sensing, medical imaging, and astronomical image construction. The main problem is the accurate alignment of multiple images of the same scene, which can vary in terms of time, viewpoint, or sensor used. This discrepancy often leads to errors in the registration process, affecting the quality and reliability of the final output. The existing methods and algorithms in image registration may not be able to effectively handle these complexities, leading to issues such as inaccurate alignment, loss of information, and reduced overall performance. These limitations highlight the need for a more robust and reliable system that can address the challenges in image registration and produce accurate results from the available image data.

Through the development of a specialized system, there is an opportunity to improve the efficiency and effectiveness of image registration processes, ultimately benefiting various applications in different domains.

Objective

The objective of this project is to develop an image registration system using Fourier-Mellin Transformation to accurately align images from different domains, such as remote sensing, medical imaging, and astronomical image construction. The system aims to enhance the quality of registered images through a high pass filter and provide a user-friendly interface for efficient user interaction. By addressing the challenges in existing image registration methods and showcasing the significance of such systems in various applications, this project seeks to improve the efficiency and effectiveness of image alignment processes. The choice of MATLAB as the software platform is based on its robust capabilities in image and signal processing, making it suitable for implementing complex algorithms like Fourier-Mellin Transformation.

Proposed Work

The proposed project aims to develop an image registration system that addresses the challenges in aligning images from diverse domains efficiently. By utilizing Fourier-Mellin Transformation, the system will implement the image alignment process and enhance the quality of the registered images through a high pass filter. The rationale behind choosing this technique is its proven effectiveness in accurately aligning images even in the presence of noise or other distortions. The system will provide a graphical user interface to facilitate user interaction and showcase the capabilities of the system in a user-friendly manner. In addressing the gap in existing literature regarding image registration systems, the project will demonstrate the significance of such systems across various domains, highlighting their applications in remote sensing, medical imaging, and astronomical image construction.

By developing a flexible system that allows users to select, register, and combine multiple images, the project aims to provide a comprehensive solution for efficient image alignment. The choice of MATLAB as the software platform for this project is based on its robust capabilities in image processing and signal processing, making it well-suited for implementing complex algorithms like Fourier-Mellin Transformation for image registration.

Application Area for Industry

This project can be utilized in various industrial sectors such as agriculture, where it can be applied in the analysis of satellite images for crop monitoring and yield prediction. In the healthcare industry, the image registration system can assist in aligning medical images for accurate diagnosis and treatment planning. It can also be beneficial in the automotive sector for quality control by aligning images of car components during the production process. Additionally, in the field of robotics, the system can be used for image fusion from different sensors to improve perception and decision-making abilities. The proposed image registration system addresses the challenges faced by industries in aligning images from different sources or time points, enabling more accurate analysis and decision-making processes.

By implementing Fourier-Mellin Transformation and a high pass filter, the system offers a reliable and efficient solution to the complex task of image registration. The benefits of using this system include improved accuracy in image alignment, enhanced data interpretation, and increased efficiency in various industrial applications. Its user-friendly GUI allows for easy selection and processing of images, making it a versatile tool for different domains requiring image registration capabilities.

Application Area for Academics

The proposed project on image registration using Fourier-Mellin Transformation can significantly enrich academic research, education, and training in the field of computer vision. This project can serve as a valuable tool for researchers, MTech students, and PHD scholars looking to explore innovative research methods and techniques in image processing and analysis. The relevance of this project lies in its potential applications across various domains such as remote sensing, medical imaging, and astronomical imaging. The developed system can be used to align images from different sources, thereby enabling researchers to extract useful information and insights from the data. The GUI-based system also makes it user-friendly and accessible for educational purposes, allowing students to understand the concepts of image registration and explore different techniques in a practical manner.

Researchers in the field of computer vision can utilize the code and literature of this project to enhance their work in image processing and data analysis. The implementation of Fourier-Mellin Transformation in MATLAB provides a solid foundation for further research and experimentation in image registration techniques. MTech students and PHD scholars can leverage the system to conduct simulations, analyze data, and explore new methodologies for enhancing image alignment and processing. The future scope of this project includes expanding the system to support more sophisticated image registration algorithms, incorporating machine learning techniques for improved accuracy, and integrating it with other software platforms for enhanced functionality. This project paves the way for exploring new research avenues in image registration and data analysis, contributing to the advancement of knowledge in computer vision and related fields.

Algorithms Used

The primary algorithmic framework used in this project is the Fourier-Mellin Transformation. This algorithm is chosen for its effectiveness in estimating the four degrees of freedom for the images. It is implemented in the main code and utilized to perform transformation operations on the chosen images, aiding in effective image registration. The proposed work is to create an image registration system, which implements the image aligning process through a method named Fourier-Mellin Transformation. The system provides a GUI allowing users to select one reference image and one other image for registration.

Upon selecting the images and executing the algorithm, the system applies transformation operations on the images, and a high pass filter, to generate the final, registered image. This system is flexible, permitting the selection, registration and combining of multiple images using the implemented techniques.

Keywords

image registration, computer vision, Fourier-Mellin transformation, remote sensing, medical imaging, astronomical imaging, graphical user interface, MATLAB, high pass filtration, diagnostic imaging, chest imaging, lung imaging, cardiac registration, transformation

SEO Tags

Image Registration, Computer Vision, Fourier-Mellin Transformation, Remote Sensing, Medical Imaging, Astronomical Imaging, Graphical User Interface, MATLAB, High Pass Filtration, Diagnostic Imaging, Chest Imaging, Lung Imaging, Cardiac Registration, Transformation, Image Alignment, Image Processing, Research Scholar, PHD Student, MTech Project, Image Analysis, Computer Science, Signal Processing, Algorithm Development, Research Methodology, Data Visualization, Data Analysis, Image Fusion, Image Enhancement, Image Segmentation, Image Recognition.