A Comprehensive Survey on Image Filtering & Inpainting for Improved Image Quality
Kalpana Patil, Varsha Bendre · 2023
Computer vision has significantly impacted information technology over the last few years. The image processing process lays the groundwork for computer vision with important components, including image filtering and image inpainting. Digital image processing is one of the broadest areas for study. It has several applications in military, medicine, space, automobile, security systems and many others. To increase the effectiveness of the system's noise suppression structural similarity index, universal image quality index, texture detection, mean square error, peak signal-to-noise ratio, and many other metrics. The evolutionary examination of several image-filtering methods is included in this paper. Among these methods, the most significant are median filtering, pixel similarity weighted frame averaging, bilateral filtering, anisotropic diffusion, and Gaussian filtering. This study focuses on an evolutionary analysis of image inpainting methods based on parallel pipelines, convolution neural networks and generative adversarial networks. The analysis of numerous works on improving image quality reveals that the hybrid model of image-filtering and image inpainting for image quality improvement is the promising solution for improved quality of image required for computer vision applications.