Recently, image prior learning has emerged as an effective tool for image denoising, which
exploits prior knowledge to obtain sparse coding models and utilize them to reconstruct the …

We propose a non-iterative image deconvolution algorithm for data corrupted by Poisson or
mixed Poisson-Gaussian noise. Many applications involve such a problem, ranging from …

In this paper, we have proposed adaptive methods for image restoration in which the input
images are affected by noise which is removed by fuzzy based median filter (FMF). The …

In this work we present a framework of designing iterative techniques for image deblurring in
inverse problem. The new framework is based on two observations about existing methods …

In this article, a focus is laid on the hybridization of various noise removal kernels that are
used in the normalization of the noise in the medical MR images which is acquainted into …

QR codes are widely used in the traceability of commodities, but the QR codes are easy to
become blurred during the acquisition process of mobile phones, which affects their normal …

Image denoising is essential to extract the information contained in an image without errors.
A technique of using both wavelets and evolutionary computing tools is proposed to denoise …

Medical image denoising plays a critical role in enhancing the quality of diagnostic imaging,
where noise reduction without compromising image details is paramount. In this paper, we …

The Kalman filter is a classical algorithm of estimation and control theory. Its use in image
processing is not very well known as it is not its typical application area. The paper deals …

Noise removal and restoration are important topics in image processing. The filter-based
denoising techniques can effectively reduce the image noise but sometimes lose image …