MATLAB Image Processing Implementation with Code Examples

Image processing represents a widely utilized technology encompassing various techniques such as image restoration, TV (Total Variation) models, and hole-filling algorithms for image completion tasks. This discipline investigates methodologies for image enhancement, reconstruction, and modification, holding significant applications across multiple domains. Through MATLAB implementations, we can apply techniques like the TV model which minimizes total variation using gradient descent optimization, often implemented through functions like `imfilter()` for convolution operations and `gradient()` for derivative calculations. Image hole-filling algorithms typically employ region-growing methods or PDE-based approaches using functions such as `regionfill()` or custom implementations of inpainting algorithms. These processing techniques enable quality improvement of degraded images, restoration of damaged visual data, and specific target recognition tasks. Consequently, image processing remains fundamentally crucial for numerous industries including medical imaging, computer vision, and remote sensing applications.