A new approach reconstruction texts of noisy images based on algorithms P-Norm and descending gradient

With the increasing advancement of knowledge, the rate of information exchange has increased dramatically. A large amount of this information is in the form of images, which shows the importance of image processing. due to the random physical nature of imaging systems, noise in the image is unavoidable This makes it difficult to perform various image processes such as segmentation, recognition and interpretation .Searching to remove noise from digital images is a challenge, In this research, a combined method for reconstructing texts in noise imaging using two P-Norm techniques and gradient technique is presented. The purpose of this article is to blur and unmute a noise image so that the amount of noise in the output image is minimized or completely noise-free. Because the PNorm method works very well in removing noise from images with high noise distribution. First, the P-Norm technique is performed on the photo to improve the image quality in the best possible way. The descending gradient algorithm is then used to re-filter to remove residual noise to ensure that any potential noise in the final image is removed. In the simulation, three images with text were used, which showed the results of this simulation The combination of these two methods effectively restores the lost quality of the images so that the full readability of the writings results.