Abstract: Image processing is one of the interesting topics of research in mathematics and engineering. In last few decades partial differential equation (PDE) based image processing has attracted the researchers because of the sound theoretical and numerical background of PDEs. The PDE models give the insight into the physical phenomena and help to come up with new models and effective numerical methods to solve it. Most of the PDE models of initial days are of lower order but they have some drawbacks such as blocky effect in denoising, failure with large gap in inpainting. Higher order PDE models have shown promise to overcome these defects. So the idea is to look for appropriate higher order PDE models to deal with the problems that occurred in the field of image processing. In this talk, we will focus on three different types of image processing problems namely image denoising, inpainting and segmentation via higher order PDE models and will share with you the developments which we have made on theoretical and computational fronts towards better PDE based image analysis.