Image Denoising Method Based on Directional Total Variation Filtering

Image restoration and reconstruction from blurry and noisy images have proved to be challenging problem. Noise removal plays any important role in preserving the meaningful and useful information in images. Our paper is based on a denoising technique known as total variation (TV). Over the years, high quality images and videos have become a trend. However, noise has remained an integral part in images and videos. Many denoising techniques have been developed over the time to remove noise from images and videos. Linear filters, Non-Linear filters, median filters and their modifications, have been a great success in noise removal. However, they resulted in blurring of images. We came up with a directional total variation algorithm for denoising. Over the past, most of the denoising methods have been used with noisy images. In our study, we make use of sequential 1D total variation on the pixel sequence procured in various positions along with horizontal, vertical and zig-zag. The evaluation of our proposed approach is performed based on standard test images and the nature of the denoised images is measured by making use of objective matrices like visual signal to noise ratio (VSNR), and peak signal to noise ratio. Numerous experiments proved that our proposed method yields promising results.