We propose a robust image enhancement algorithm dedicated for muscle fiber specimen images captured by optical microscopes. Blur or out of focus problems are prevalent in muscle images during the image acquisition stage. Traditional image deconvolution methods do not work since they assume the blur kernels are known and also produce ring artifacts. We provide a compact framework which involves ...

In many applications, observed signals are contaminated by both random noise and blur. This paper proposes a blind deconvolution procedure for estimating a regression function with possible jumps preserved, by removing both noise and blur when recovering the signals. Our procedure is based on three local linear kernel estimates of the regression function, constructed from observations in a left...

In this paper, a new method for the identification and removal of image artefacts caused by linear motion blur is presented. By transforming the image into the frequency domain and computing its logarithmic power spectrum, the algorithm identifies the parameters describing the camera motion that caused the blur. The spectrum is analysed using an adjusted version of the Radon transform and a str...

In depth from defocus (DFD), when images are captured with different camera parameters, a relative magnification is induced between them. Image warping is a simpler solution to account for magnification than seemingly more accurate optical approaches. This work is an investigation into the effects of magnification on the accuracy of DFD. We comment on issues regarding scaling effect on relative...

This is a survey of recent developments in smoothing parameter selection for curve estimation. The first goal of this paper is to provide an introduction to the methods available, with discussion at both a practical and also a nontechnical theoretical level, including comparison of methods. The second goal is to provide access to the literature, especially on smoothing parameter selection, but ...

Medical images such as computed tomography (CT) are degraded by different types of blur due to the imperfect resolution of the imaging system, data loss at the acquisition time and other technical reasons. The fastest way to deblur an image is by convolving a special kernel to the corrupted image. Laplacian kernels are famous and widely used in this field, but the issue is only few kernels are ...

Image Restoration is the method of recovering original image from degraded image and also to understand the image without any artifact errors. Image restoration methods can be considered as direct and indirect techniques. Direct techniques are used when restoration results are generated in a simple one step fashion. Similarly, indirect techniques are used when restoration results are obtained a...

Motion blur, which increases the difficulty of locating and identifying target objects, has always been an ill-posed issue of space-based imaging system. In our paper, we point out the issue of deblurring degraded images caused by relative motion between space-based imaging system and observation targets. Such as motion of target objects to be observed or tremors of space-based imaging system. ...

This thesis addresses total variation (TV) image restoration and blind image deconvolution. Classical image processing problems, such as deblurring, call for some kind of regularization. Total variation is among the state-of-the-art regularizers, as it provides a good balance between the ability to describe piecewise smooth images and the complexity of the resulting algorithms. In this thesis, ...