Contacts: Tel: (65)-6516-6250 Office: S14-05-21 Email: [email protected] I mage restoration refers to the process of recovering an ideal image from its corrupted version which is the one we actually observe. The corruptions may be due to noise along the way of acquisition, out-of-focus of the imaging device, or packet loss during transmission of an acquired image from one location to another. ...

Several mathematical methods are discussed in this paper, which are applied in image compression and restoration. Singular value decomposition (SVD) is used in compressing image. Conjugate gradients (CG) method and truncated Singular value decomposition (TSVD) regularization method are applied in image restoration. From the experience results we can see that those methods are effective in image...

A new method, based on the normal shrink and modified version of Katssagelous and Lay, is proposed for multiscale blind image restoration. The method deals with the noise and blur in the images. It is shown that the normal shrink gives the highest S/N (signal to noise ratio) for image denoising process. The multiscale blind image restoration is divided in two sections. The first part of this pa...

This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the...

Mechanical vibrations are often the principal cause of image degradation. Low temporal-frequency mechanical vibrations involve random image degradation that depends on the instant of exposure. Exact restoration requires the calculation of a specific filter unique to each vibrated image. To calculate the restoration filter for each image, one needs the specific optical transfer function unique t...

The restoration problem deals with images in which information has been destroyed or obscured. In this paper, we present a framework for addressing image restoration problems in which the goal is to recover information about the image. Restoration algorithms often use tentative assumptions to compensate for the information lost in the degradation process. We propose cross-validation as a method...

Image restoration deals with bringing back the degraded image to its original state i.e. it helps to restore the degraded image into more sharp and clear image. This research paper proposes a novel and improved restoration technique using blind image deconvolution and curvelet transform. A degraded image contains some unwanted things like noise and blur. The main goal of the restoration algorit...

Numerous image restoration approaches have been proposed based on attention mechanism, achieving superior performance to convolutional neural networks (CNNs) counterparts. However, they do not leverage the model in a form fully suited tasks. In this paper, we propose an network with novel called cross-scale <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/19...