Restoration for blurred noisy images based on guided filtering and inverse filter

Abstract

The development of complex life leads into a need using images in several fields, because these images degraded during capturing the image from mobiles, cameras and persons who do not have sufficient experience in capturing images. It was important using techniques differently to improve images and human perception as image enhancement and image restoration etc. In this paper, restoration noisy blurred images by guided filter and inverse filtering can be used for enhancing images from different types of degradation was proposed. In the color images denoising process, it was very significant for improving the edge and texture information. Eliminating noise can be enhanced by the image quality. In this article, at first, The color images were taken. Then, random noise and blur were added to the images. Then, the noisy blurred image passed to the guided filtering to get on denoised image. Finally, an inverse filter applied to the blurred image by convolution an image with a mask and getting on the enhanced image. The results of this research illustrated good outcomes compared with other methods for removing noise and blur based on PSNR measure. Also, it enhanced the image and retained the edge details in the denoising process. PSNR and SSIM measures were more sensitive to Gaussian noise than blur.

Integrated NIR-HE based SPOT-5 image enhancement method for features preservation and edge detection

“…As a result, PSNR and MSE are interrelated. Where there is higher PSNR and lower MSE, a better contrast can be achieved [98], [171], [195]- [199]. Table 2 shows a comparison of PSNR and MSE results, when using the different methods.…”