Least square based image deblurring

An image can be basically defined as an object that represents visual observation, which can be created and stored in the electronic form, produced from an optical device. When we take a photograph, there can be many problems associated with that particular image. Among them, one of the main issue is the blur of the image. Blur can be defined as something which will become vague or less distinct. A blurred image looks sharper or more detailed, if we are able to perceive all the objects and their shapes correctly in it. The main cause for blur is the out of focus issue of the camera/sensor. An image which is in out of focus will appear in a blurred state. Even if, at the present time, with an auto focus facility, sometimes we will not get the image in the correct focus. Most probably, a part of the image will be crisp and clear, however rest will be ill-defined. Image deblurring is a common and important process in fields like digital photography, medical imaging and astronomy. Hence, removing or dropping the total amount of blur is the most important task before being applying to the image analysis techniques. In this paper, a colour image deblurring algorithm based on the concept of least squares is proposed. The 1D least square based deconvolution technique is extended to colour image deblurring. The proposed approach is experimented on standard test images and the results are compared with classical total variation image deblurring algorithm. The effectiveness of the proposed approach is evaluated in terms of standard quality metrics such as PSNR and SSIM.