Image Restoration

This book offers an updated perspective on image restoration, focusing on algorithms and their applications in various fields, including Image Restoration techniques.

In Image Restoration, the author addresses the urgent need to refresh existing references on image restoration, many of which have become outdated. This comprehensive overview delves into recent breakthroughs in algorithm development that have significant implications for various scientific and engineering applications, including astronomical imaging, medical imaging, and photo editing. The text illustrates how these advancements not only enhance practical applications but also provide novel insights into the fundamental properties of image sources, enriching the field as a whole.

The book effectively balances core principles with the latest technological advancements in imaging, computing, and communications. It emphasizes the importance of reproducibility in research, allowing scholars to build upon one another's work, which ultimately strengthens the technical community. The content is structured to be as experimentally reproducible as possible, ensuring that readers can engage with the material in a meaningful way.

Key topics covered include image denoising and deblurring, various restoration methods, blind restoration under space-varying blur, super-resolution techniques, learning-based methods, and multi-spectral image restoration. The text also explores new possibilities offered by hybrid imaging systems. By focusing on algorithms rather than theories or applications, Image Restoration fills a crucial gap in the literature, offering access to downloadable source code that illustrates fundamental techniques and the current state of the art in image restoration, making it an invaluable resource for readers of all expertise levels.