Image Restoration of Damaged Mural images based on Image Decomposition - Rathika, M; Shenbagavalli, R (International Journal of Computer Sciences and Engineering, 2025)
The most significant challenges in image processing and pattern recognition is image decomposition and restoration. Image Restoration is the operation of taking a noisy image and estimating the clean, original image. Corrupt image may come in many forms such as motion blur, noise and camera mis-focus. Restoration is a process of eliminating degraded noise and increases the quality of image. Image decomposition is to decompose an image into its component structures. When two image signals are considered, a combined image signal should contain the image structure of both these signals In this paper, the mural images are decomposed into cartoon component or geometrical part of blurred images and Texture component or small scale special pattern using Bilateral filter. In cartoon component augmented Lagrangian method has been used to fill the missing pixel. In texture component the blurring can be removed using median filter and conservative filter. Median filter is used to remove noise and conservative filter is used for smoothening the image. By using these filters, degraded mages can be restored successfully. The restoration efficiency can be measured with MSE (Mean Square error) and PSNR (Peak Signal to Noise Ratio) parameter. Various mural images have been analyzed and tested. The accuracy is comparatively better than the existing