5,463 research outputs found
Recent Progress in Image Deblurring
This paper comprehensively reviews the recent development of image
deblurring, including non-blind/blind, spatially invariant/variant deblurring
techniques. Indeed, these techniques share the same objective of inferring a
latent sharp image from one or several corresponding blurry images, while the
blind deblurring techniques are also required to derive an accurate blur
kernel. Considering the critical role of image restoration in modern imaging
systems to provide high-quality images under complex environments such as
motion, undesirable lighting conditions, and imperfect system components, image
deblurring has attracted growing attention in recent years. From the viewpoint
of how to handle the ill-posedness which is a crucial issue in deblurring
tasks, existing methods can be grouped into five categories: Bayesian inference
framework, variational methods, sparse representation-based methods,
homography-based modeling, and region-based methods. In spite of achieving a
certain level of development, image deblurring, especially the blind case, is
limited in its success by complex application conditions which make the blur
kernel hard to obtain and be spatially variant. We provide a holistic
understanding and deep insight into image deblurring in this review. An
analysis of the empirical evidence for representative methods, practical
issues, as well as a discussion of promising future directions are also
presented.Comment: 53 pages, 17 figure
Hyperspectral image analysis for questioned historical documents.
This thesis describes the application of spectroscopy and hyperspectral image
processing to examine historical manuscripts and text. Major activities
in palaeographic and manuscript studies include the recovery of illegible or
deleted text, the minute analyses of scribal hands, the identification of inks
and the segmentation and dating of text. This thesis describes how Hyperspectral
Imaging (HSI), applied in a novel manner, can be used to perform
quality text recovery, segmentation and dating of historical documents. The
non-destructive optical imaging process of Spectroscopy is described in detail
and how it can be used to assist historians and document experts in
the exemption of aged manuscripts. This non-destructive optical method
of analysis can distinguish subtle differences in the reflectance properties of
the materials under study. Many historically significant documents from
libraries such as the Royal Irish Academy and the Russell Library at the
National University of Ireland, Maynooth, have been the selected for study
using the hyperspectral imaging technique. Processing techniques have are
described for the applications to the study of manuscripts in a poor state
of conservation. The research provides a comprehensive overview of Hyperspectral
Imaging (HSI) and associated statistical and analytical methods,
and also an in-depth investigation of the practical implementation of such
methods to aid document analysts. Specifically, we provide results from employing
statistical analytical methods including principal component analysis
(PCA), independent component analysis (ICA) and both supervised and automatic
clustering methods to historically significant manuscripts and text
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such as Leabhar na hUidhre, a 12th century Irish text which was subject to
part-erasure and rewriting, a 16th Century pastedown cover, and a multi-ink
example typical of that found in, for example, late medieval administrative
texts such as Gttingen’s kundige bok. The purpose of which is to achieve
an overall greater insight into the historical context of the document, which
includes the recovery or enhancement of faded or illegible text or text lost
through fading, staining, overwriting or other forms of erasure. In addition,
we demonstrate prospect of distinguishing different ink-types, and furnishing
us with details of the manuscript’s composition, all of which are refinements,
which can be used to answer questions about date and provenance. This process
marks a new departure for the study of manuscripts and may provide
answer many long-standing questions posed by palaeographers and by scholars
in a variety of disciplines. Furthermore, through text retrieval, it holds
out the prospect of adding considerably to the existing corpus of texts and
to providing very many new research opportunities for coming generations
of scholars
Recent Progress in Image Deblurring
This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques share the same objective of inferring a latent sharp image from one or several corresponding blurry images, while the blind deblurring techniques are also required to derive an accurate blur kernel. Considering the critical role of image restoration in modern imaging systems to provide high-quality images under complex environments such as motion, undesirable lighting conditions, and imperfect system components, image deblurring has attracted growing attention in recent years. From the viewpoint of how to handle the ill-posedness which is a crucial issue in deblurring tasks, existing methods can be grouped into five categories: Bayesian inference framework, variational methods, sparse representation-based methods, homography-based modeling, and region-based methods. In spite of achieving a certain level of development, image deblurring, especially the blind case, is limited in its success by complex application conditions which make the blur kernel hard to obtain and be spatially variant. We provide a holistic understanding and deep insight into image deblurring in this review. An analysis of the empirical evidence for representative methods, practical issues, as well as a discussion of promising future directions are also presented
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