Fisheye Image Distortion Correction Using MATLAB

Implementing fisheye image distortion correction through MATLAB proves to be a highly effective approach. The process involves calibrating fisheye lens distortion parameters (typically using Zhang's calibration method or similar techniques) and applying inverse distortion transformation to eliminate bending effects in original images. Post-correction, linear interpolation algorithms (such as bilinear interpolation) are employed to fill pixel gaps in the rectified images, ensuring smoother transitions and more natural visual output. The MATLAB implementation typically utilizes functions like `undistortFisheyeImage()` from the Computer Vision Toolbox or custom transformation matrices with `interp2()` for interpolation. This methodology significantly enhances fisheye image quality by restoring geometric accuracy and improving edge continuity, enabling observers to better interpret and analyze image content. Therefore, leveraging MATLAB for distortion correction and interpolation processing represents a highly recommended strategy when working with fisheye imagery.