Faster Deblurring for Digital Images using an Ameliorated Richardson-Lucy Algorithm

Blur is one popular artifact that degrades digital images due to various unavoidable reallife limitations. Image deblurring is the recovery of an acceptable-quality image from a blurry image. This topic has been a major research focus because of the noticeable upsurge in the use of digital images and imaging systems in many real-world applications. Many intricate and simple algorithms exist for image deblurring. Accordingly, the Richardson–Lucy (RL) algorithm is highly renowned in the field of image deblurring. However, it requires numerous iterations in many situations to produce results with sharp attributes. Hence, an ameliorated RL algorithm is proposed in this article to accelerate the deblurring process by reducing the number of required iterations. The key novelties of the proposed algorithm lie in the addition of a specially designed acceleration factor and in raising part of the algorithm to the power of two. These modifications are achieved experimentally, in which they significantly reduced the number of required iterations to obtain the desired results. Intensive experiments on naturally and synthetically-blurred images reveal that the proposed algorithm performs better than the original and accelerated counterparts in terms of recorded accuracy, perceived quality, and processing speed.