• Priya Khatri
• Manish Gupta
• Dr Anshuj Jain

Restoration of spatially varying blur images is a critical challenge in the field of image processing and computer vision. Unlike uniform blur, spatially varying blur arises from non-uniform motion, depth variations, or lens aberrations, making its restoration a highly complex task. This review explores various techniques and methodologies for restoring images affected by spatially varying blur using a single input image. The paper delves into the mathematical modeling of spatially varying blur, covering topics such as point spread functions (PSF), kernel estimation, and optimization-based restoration methods. Additionally, it examines the integration of deep learning and artificial intelligence techniques for addressing this problem, emphasizing their potential for improved accuracy and efficiency. The review highlights the limitations, advantages, and applicability of these techniques in real-world scenarios such as photography, medical imaging, and remote sensing.

Restoration, Spatially, Blur, Image PSF

"Review of Restoration of Spatially Varying Blur Image From A Single Image", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 12, page no.e679-e682, December-2024, Available :http://www.jetir.org/papers/JETIR2412476.pdf

"Review of Restoration of Spatially Varying Blur Image From A Single Image", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 12, page no. ppe679-e682, December-2024, Available at : http://www.jetir.org/papers/JETIR2412476.pdf