Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction...

Many conventional blind image deconvolution algorithms have much processing time because the consideration of various cases and the optimization are required for general employment. Moreover, these algorithms are also complex to deal with various point spread functions (PSF). Therefore, this paper restricts the type of PSF to the dual-exposure type and proposes effective PSF search algorithm, u...

To separate out the noise behaviour from color image several approaches has been identified, adaptive filter which is extension of LMS filter is one of them to achieve higher signal to noise ratio. In this paper, comparison of adaptive filter with different structure and two dimensional block processing for color image noise abolition is proposed. Simulations for different block size as well as...

An effective way to implement image processing applications is to use embedded processors with dynamically reconfigurable accelerator cores. The processing speed of these processors are not only depends on the parallelism, but also depend on the local memory utilization since the local memories are much faster than the global memory. In this paper, we accelerate the optical-flow extraction algo...

In this paper, we propose a general formulation of discrete functional regularization on weighted graphs. This framework can be used to on any multi-dimensional data living on graphs of arbitrary topologies. But, in this work, we focus on the microscopic image segmentation and classification with a semi and unsupervised schemes. Moreover, to provide a fast image segmentation we propose a graph ...

Image segmentation is a fundamental step in many of image processing applications. In most cases the image’s pixels are clustered only based on the pixels’ intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering the importance of including spatial information of pixels which improves the quality of image segmentati...

Artifact is one of the most important factors in degrading the CT image quality and plays an important role in diagnostic accuracy. In this paper, some artifacts typically appear in Spiral CT are introduced. The different factors such as patient, equipment and interpolation algorithm which cause the artifacts are discussed and new developments and image processing algorithms to prevent or reduc...