ASIFT Implementation on MATLAB with Enhanced Features

This ASIFT program on MATLAB has been substantially improved from its original version. The enhanced implementation not only excels in image recognition and matching tasks, but also shows remarkable performance gains compared to conventional algorithms such as SIFT and SURF. Through the integration of novel algorithmic approaches and optimization of existing code structures, I have achieved more stable and reliable performance metrics. Key implementation enhancements include: - Advanced affine transformation handling through improved parameterization of camera orientation angles - Optimized feature detection pipeline with better scale-space extremum detection - Enhanced matching algorithm using refined distance ratio tests and geometric consistency checks Additionally, several supplementary functions have been integrated, such as automatic brightness and contrast adjustment modules that employ histogram equalization techniques to improve image preprocessing quality. The program utilizes MATLAB's image processing toolbox functions like imadjust() and histeq() for these adjustments, while implementing custom functions for affine simulation and feature matching. Overall, this upgraded ASIFT implementation demonstrates superior performance in various image processing applications, providing users with more robust and accurate tools for image recognition and matching operations. The code structure maintains modularity, allowing easy integration of additional features while ensuring computational efficiency through vectorized operations and optimized memory management.