Proceedings. International Conference on Image Processing, 2002
We present an application of digital image processing for the analysis of the medieval mosaic con... more We present an application of digital image processing for the analysis of the medieval mosaic conservation. The reconstructed art piece was the "The Last Judgement" mo- saic, situated on the wall of the St. Vitus cathedral in Prague, Czech Republic. The historical photograph of the mosaic from the century was compared with the photograph of the current state. The images
Due to imperfections of imaging devices (optical degradations, limited resolution of CCD sensors)... more Due to imperfections of imaging devices (optical degradations, limited resolution of CCD sensors) and instability of the observed scene (object motion, media turbulence), acquired images are often blurred, noisy and may exhibit insufficient spatial and/or temporal resolution. Such images are not suitable for object detection and recognition. Reliable detection requires recovering the original image. If multiple images of the scene are available, this can be achieved by image fusion.
2013 IEEE International Conference on Image Processing, 2013
ABSTRACT We propose a method for removal of space-variant blur from images predominantly degraded... more ABSTRACT We propose a method for removal of space-variant blur from images predominantly degraded by camera shake without any knowledge of camera trajectory. Blurs are first estimated in a small number of image patches. We derive a novel parametric blur interpolation method and discuss conditions under which it can be used to exactly calculate blurs for every pixel position. Having this information, we restore the sharp image by a standard regularization technique. Performance of the proposed method is experimentally validated.
Proceedings of SPIE - The International Society for Optical Engineering, 2005
The term fusion means in general an approach to combine the important information simultaneously ... more The term fusion means in general an approach to combine the important information simultaneously from several sources (channels). When we approach image fusion, multiscale transforms (MST) are commonly used as the analyzing tool. It transforms the sources into a space-frequency domain which can be understood as a measure of the saliency (activity level). The criterion to fuse consists of taking the decision to preserve the most salient data from the sources. In order to reduce sensitivity against noise the saliency is often averaged over certain neighborhood (window). However averaging produces that decisions become more fuzzy. Traditionally the size of the neighborhood is chosen fixed according to the level of noise present in the sources, which has to be estimated in advance. This paper proposes a novel technique which combines a set of decreasing averaging windows in order to exploit the advantages of each one. We call it multisize windows-based fusion. This technique apart from improving fusion results avoids selecting the neighboring size in advance (and therefore to estimate the level of noise) since it only needs a simple set of windows defined according to image size. We compared it with another technique developed by us called oriented windows which, although it consider a fixed neighborhood, adapts the averaging shape to the spatial orientation of the saliency. The specific case of multifocus image fusion is considered for the experiments. The multisize windows technique delivers the best percentage of correct decisions compared with any single fixed window in all the experiments carried out, adding different noise sources (Gaussian, speckle and salt&pepper) with different levels. Although it does not performs better than the oriented window scheme one has to bear in mind that oriented windows are tuned in each case to the best size.
Advanced Signal Processing Algorithms, Architectures, and Implementations Xviii, 2008
Imaging plays a key role in many diverse areas of application, such as astronomy, remote sensing,... more Imaging plays a key role in many diverse areas of application, such as astronomy, remote sensing, microscopy, and tomography. Owing to imperfections of measuring devices (e.g., optical degradations, limited size of sensors) and instability of the observed scene (e.g., object motion, media turbulence), acquired images can be indistinct, noisy, and may exhibit insufficient spatial and temporal resolution. In particular, several external effects blur images. Techniques for recovering the original image include blind deconvolution (to remove blur) and superresolution (SR). The stability of these methods depends on having more than one image of the same frame. Differences between images are necessary to provide new information, but they can be almost unperceivable. State-of-the-art SR techniques achieve remarkable results in resolution enhancement by estimating the subpixel shifts between images, but they lack any apparatus for calculating the blurs. In this paper, after introducing a review of current SR techniques we describe two recently developed SR methods by the authors. First, we introduce a variational method that minimizes a regularized energy function with respect to the high resolution image and blurs. In this way we establish a unifying way to simultaneously estimate the blurs and the high resolution image. By estimating blurs we automatically estimate shifts with subpixel accuracy, which is inherent for good SR performance. Second, an innovative learning-based algorithm using a neural architecture for SR is described. Comparative experiments on real data illustrate the robustness and utilization of both methods.
This work presents a new method for motion estimation of tagged cardiac magnetic resonance sequen... more This work presents a new method for motion estimation of tagged cardiac magnetic resonance sequences based on variational techniques. The variational method has been improved by adding a new term in the optical flow equation that incorporates tracking points with high stability of phase. Results were obtained through simulated and real data, and were validated by manual tracking and with respect to a reference state-of-the-art method: harmonic phase imaging (HARP). The error, measured in pixels per frame, obtained with the proposed variational method is one order of magnitude smaller than the one achieved by the reference method, and it requires a lower computational cost.
ABSTRACT Scitation is the online home of leading journals and conference proceedings from AIP Pub... more ABSTRACT Scitation is the online home of leading journals and conference proceedings from AIP Publishing and AIP Member Societies
Historical documents often undergo various changes over time, that alter their original state and... more Historical documents often undergo various changes over time, that alter their original state and reduce their legibility. Digital techniques are widely applied for document preservation, archiving, analysis and dissemination over the Internet. The goal of restoration is to improve the document legibility for both human and automatic operators, to extract patterns and enhance colour reproduction. Our paper presents a framework for virtual restoration of ancient documents based on a combination of multispectral acquisition, 3D imaging and digital image analysis. The proposed framework consists of several steps. First, digital representations of the documents are acquired as multispectral images and 3D surface maps, the latter reconstructed by a structured light technique. A multispectral camera and a digital projector are used in triangular configuration for 2D and 3D data acquisition. Then the multispectral images are registered against possible misalignments, and the 3D surface representation is used to correct geometrical distortions. Document flattening is then performed by 3D surface parameterization and texture mapping. Statistical techniques of decorrelation are applied to extract individual context parts of the document patterns (stamp, text, etc.) and to attenuate interferences. The processed data are then binarized by the proper segmentation technique. The entire digital object history -all the acquisition and processing steps, with the corresponding parameters -is stored in metadata files. These data can be exploited in a future evaluation of the restoration process and can be used for either the creation of an expert knowledge database or the extraction of cross-document observations and conclusions.
We present an application of digital image processing for an analysis of medieval mosaic conserva... more We present an application of digital image processing for an analysis of medieval mosaic conservation. The reconstructed art piece was "The Last Judgment" mosaic, situated on the wall of the St. Vitus cathedral in Prague, Czech Republic. The historical photograph of the mosaic from the 19 th century was compared with the photograph of the current state. The images were firstly preprocessed to increase their quality (noise reduction, deblurring). In the second stage, geometrical differences between images were removed by means of image registration techniques -mutual information and feature point correspondence. Finally, differences of the current and historical photographs were identified.
Proceedings. International Conference on Image Processing, 2002
We present an application of digital image processing for the analysis of the medieval mosaic con... more We present an application of digital image processing for the analysis of the medieval mosaic conservation. The reconstructed art piece was the "The Last Judgement" mo- saic, situated on the wall of the St. Vitus cathedral in Prague, Czech Republic. The historical photograph of the mosaic from the century was compared with the photograph of the current state. The images
Due to imperfections of imaging devices (optical degradations, limited resolution of CCD sensors)... more Due to imperfections of imaging devices (optical degradations, limited resolution of CCD sensors) and instability of the observed scene (object motion, media turbulence), acquired images are often blurred, noisy and may exhibit insufficient spatial and/or temporal resolution. Such images are not suitable for object detection and recognition. Reliable detection requires recovering the original image. If multiple images of the scene are available, this can be achieved by image fusion.
2013 IEEE International Conference on Image Processing, 2013
ABSTRACT We propose a method for removal of space-variant blur from images predominantly degraded... more ABSTRACT We propose a method for removal of space-variant blur from images predominantly degraded by camera shake without any knowledge of camera trajectory. Blurs are first estimated in a small number of image patches. We derive a novel parametric blur interpolation method and discuss conditions under which it can be used to exactly calculate blurs for every pixel position. Having this information, we restore the sharp image by a standard regularization technique. Performance of the proposed method is experimentally validated.
Proceedings of SPIE - The International Society for Optical Engineering, 2005
The term fusion means in general an approach to combine the important information simultaneously ... more The term fusion means in general an approach to combine the important information simultaneously from several sources (channels). When we approach image fusion, multiscale transforms (MST) are commonly used as the analyzing tool. It transforms the sources into a space-frequency domain which can be understood as a measure of the saliency (activity level). The criterion to fuse consists of taking the decision to preserve the most salient data from the sources. In order to reduce sensitivity against noise the saliency is often averaged over certain neighborhood (window). However averaging produces that decisions become more fuzzy. Traditionally the size of the neighborhood is chosen fixed according to the level of noise present in the sources, which has to be estimated in advance. This paper proposes a novel technique which combines a set of decreasing averaging windows in order to exploit the advantages of each one. We call it multisize windows-based fusion. This technique apart from improving fusion results avoids selecting the neighboring size in advance (and therefore to estimate the level of noise) since it only needs a simple set of windows defined according to image size. We compared it with another technique developed by us called oriented windows which, although it consider a fixed neighborhood, adapts the averaging shape to the spatial orientation of the saliency. The specific case of multifocus image fusion is considered for the experiments. The multisize windows technique delivers the best percentage of correct decisions compared with any single fixed window in all the experiments carried out, adding different noise sources (Gaussian, speckle and salt&pepper) with different levels. Although it does not performs better than the oriented window scheme one has to bear in mind that oriented windows are tuned in each case to the best size.
Advanced Signal Processing Algorithms, Architectures, and Implementations Xviii, 2008
Imaging plays a key role in many diverse areas of application, such as astronomy, remote sensing,... more Imaging plays a key role in many diverse areas of application, such as astronomy, remote sensing, microscopy, and tomography. Owing to imperfections of measuring devices (e.g., optical degradations, limited size of sensors) and instability of the observed scene (e.g., object motion, media turbulence), acquired images can be indistinct, noisy, and may exhibit insufficient spatial and temporal resolution. In particular, several external effects blur images. Techniques for recovering the original image include blind deconvolution (to remove blur) and superresolution (SR). The stability of these methods depends on having more than one image of the same frame. Differences between images are necessary to provide new information, but they can be almost unperceivable. State-of-the-art SR techniques achieve remarkable results in resolution enhancement by estimating the subpixel shifts between images, but they lack any apparatus for calculating the blurs. In this paper, after introducing a review of current SR techniques we describe two recently developed SR methods by the authors. First, we introduce a variational method that minimizes a regularized energy function with respect to the high resolution image and blurs. In this way we establish a unifying way to simultaneously estimate the blurs and the high resolution image. By estimating blurs we automatically estimate shifts with subpixel accuracy, which is inherent for good SR performance. Second, an innovative learning-based algorithm using a neural architecture for SR is described. Comparative experiments on real data illustrate the robustness and utilization of both methods.
This work presents a new method for motion estimation of tagged cardiac magnetic resonance sequen... more This work presents a new method for motion estimation of tagged cardiac magnetic resonance sequences based on variational techniques. The variational method has been improved by adding a new term in the optical flow equation that incorporates tracking points with high stability of phase. Results were obtained through simulated and real data, and were validated by manual tracking and with respect to a reference state-of-the-art method: harmonic phase imaging (HARP). The error, measured in pixels per frame, obtained with the proposed variational method is one order of magnitude smaller than the one achieved by the reference method, and it requires a lower computational cost.
ABSTRACT Scitation is the online home of leading journals and conference proceedings from AIP Pub... more ABSTRACT Scitation is the online home of leading journals and conference proceedings from AIP Publishing and AIP Member Societies
Historical documents often undergo various changes over time, that alter their original state and... more Historical documents often undergo various changes over time, that alter their original state and reduce their legibility. Digital techniques are widely applied for document preservation, archiving, analysis and dissemination over the Internet. The goal of restoration is to improve the document legibility for both human and automatic operators, to extract patterns and enhance colour reproduction. Our paper presents a framework for virtual restoration of ancient documents based on a combination of multispectral acquisition, 3D imaging and digital image analysis. The proposed framework consists of several steps. First, digital representations of the documents are acquired as multispectral images and 3D surface maps, the latter reconstructed by a structured light technique. A multispectral camera and a digital projector are used in triangular configuration for 2D and 3D data acquisition. Then the multispectral images are registered against possible misalignments, and the 3D surface representation is used to correct geometrical distortions. Document flattening is then performed by 3D surface parameterization and texture mapping. Statistical techniques of decorrelation are applied to extract individual context parts of the document patterns (stamp, text, etc.) and to attenuate interferences. The processed data are then binarized by the proper segmentation technique. The entire digital object history -all the acquisition and processing steps, with the corresponding parameters -is stored in metadata files. These data can be exploited in a future evaluation of the restoration process and can be used for either the creation of an expert knowledge database or the extraction of cross-document observations and conclusions.
We present an application of digital image processing for an analysis of medieval mosaic conserva... more We present an application of digital image processing for an analysis of medieval mosaic conservation. The reconstructed art piece was "The Last Judgment" mosaic, situated on the wall of the St. Vitus cathedral in Prague, Czech Republic. The historical photograph of the mosaic from the 19 th century was compared with the photograph of the current state. The images were firstly preprocessed to increase their quality (noise reduction, deblurring). In the second stage, geometrical differences between images were removed by means of image registration techniques -mutual information and feature point correspondence. Finally, differences of the current and historical photographs were identified.
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Papers by F. Sroubek