In the last decade, several different structured illumination microscopy (SIM) approaches have been developed. Precise determination of the effective spatial resolution in a live cell SIM reconstructed image is essential for reliable interpretation of reconstruction results. Theoretical resolution improvement can be calculated for every SIM method. In practice, the final spatial resolution of the cell structures in the reconstructed image is limited by many different factors. Therefore, assessing the resolution directly from the single image is an inherent part of the live cell imaging. There are several commonly used resolution measurement techniques based on image analysis. These techniques include full-width at half maximum (FWHM) criterion, or Fourier ring correlation (FRC). FWHM measurement requires fluorescence beads or sharp edge/line in the observed image to determine the point spread function (PSF). FRC method requires two stochastically independent images of the same observed sample. Based on our experimental findings, the FRC method does not seem to be well suited for measuring the resolution of SIM live cell video sequences. Here we show a method based on the Fourier transform analysis using power spectral density (PSD). In order to estimate the cut-off frequency from a noisy signal, we use PSD estimation based on Welch's method. This method is widely used in non-parametric power spectra analysis. Since the PSD-based metric can be computed from a single SIM image (one video frame), without any prior knowledge of the acquiring system, it can become a fundamental tool for imaging in live cell biology.
Super-resolution (SR) microscopy is a powerful technique which enhances the resolution of optical microscopes beyond the diffraction limit. Recent SR methods achieve the resolution of 100 nm. Theoretical resolution enhancement can be mathematically defined. However, the final resolution in the real image can be influenced by technical limitations. Evaluation of resolution in a real sample is essential to assess the performance of an SR technique. Several image based resolution limit evaluation methods exist, but the determination of cutoff frequency is still a challenging task. In order to compare the efficiency of assessing resolution methods, the reference estimation technique is necessary. There exist several conventional methods in digital image processing. In this paper, the most common resolution measurement techniques used in the optical microscopy imaging are presented and their performance compared.
Structured Illumination Microscopy (SIM) is a powerful super-resolution technique, which is able to enhance the resolution of optical microscope beyond the Abbe diffraction limit. In the last decade, numerous SIM methods that achieve the resolution of 100 nm in the lateral dimension have been developed. The SIM setups with new high-speed cameras and illumination pattern generators allow rapid acquisition of the live specimen. Therefore, SIM is widely used for investigation of the live structures in molecular and live cell biology.
Quantitative evaluation of resolution enhancement in a real sample is essential to describe the efficiency of super-resolution microscopy technique. However, measuring the resolution of a live cell sample is a challenging task. Based on our experimental findings, the widely used Fourier ring correlation (FRC) method does not seem to be well suited for measuring the resolution of SIM live cell video sequences. Therefore, the resolution assessing methods based on Fourier spectrum analysis are often used. We introduce a measure based on circular average power spectral density (PSDca) estimated from a single SIM image (one video frame). PSDca describes the distribution of the power of a signal with respect to its spatial frequency. Spatial resolution corresponds to the cut-off frequency in Fourier space. In order to estimate the cut-off frequency from a noisy signal, we use a spectral subtraction method for noise suppression. In the future, this resolution assessment approach might prove useful also for single-molecule localization microscopy (SMLM) live cell imaging.
Structured Illumination Microscopy (SIM) is a super-resolution technique which enables to enhance the resolution of optical microscopes beyond the diffraction limit. The final super-resolution image quality strongly depends on the performance of SIM image reconstruction. Standard SIM methods require precise knowledge of the illumination pattern and assume the sample to be stationary during the acquisition of illumination patterned images. In the case of imaging live cells, the movements of the cell result in the occurrence of image reconstruction artifacts. To reduce this kind of artifacts the short acquisition time is needed. However, short exposure time causes low signal-to-noise ratio (SNR). Moreover, a drift of the specimen may distort the illumination pattern properties in each image. This issue together with the low SNR makes the estimation of reconstruction parameters a challenging task. Inaccurate assessment of spatial frequency, phase shift or orientation of the illumination pattern leads to incorrect separation and shift of spectral components in Fourier space. This results in unwanted image reconstruction artifacts and hampers the resolution enhancement in practice. In this paper, we analyze possible artifacts in super-resolution images reconstructed using super-resolution SIM technique (SR-SIM). An overview of typical image reconstruction artifact types is presented. Distinguishing image artifacts from newly resolved sample features is essential for future SIM applications in cell biology.
The main obstacle preventing High Dynamic Range (HDR) imaging from becoming standard in image and video processing industry is the challenge of displaying the content. The prices of HDR screens are still too high for ordinary customers. During last decade, a lot of effort has been dedicated to finding ways to compress the dynamic range for legacy displays with simultaneous preservation of details in highlights and shadows which cannot be achieved by standard systems. These dynamic range compression techniques are called tone-mapping operators (TMO) and introduce novel distortions such as spatially non-linear distortion of contrast or naturalness corruption. This paper provides an analysis of objective no-reference naturalness, contrast and colorfulness measures in the context of tone-mapped images evaluation. Reliable measures of these features could be further merged together into single overall quality metric. The main goal of the paper is to provide an initial study of the problem and identify the potential candidates for such a combination.
Image sharpening is a post-processing technique employed for the artificial enhancement of the perceived sharpness by shortening the transitions between luminance levels or increasing the contrast on the edges. The greatest challenge in this area is to determine the level of perceived sharpness which is optimal for human observers. This task is complex because the enhancement is gained only until the certain threshold. After reaching it, the quality of the resulting image drops due to the presence of annoying artifacts. Despite the effort dedicated to the automatic sharpness estimation, none of the existing metrics is designed for localization of this threshold. Nevertheless, it is a very important step towards the automatic image sharpening. In this work, possible usage of full-reference image quality metrics for finding the optimal amount of sharpening is proposed and investigated. The intentionally over-sharpened "anchor image" was included to the calculation as the "anti-reference" and the final metric score was computed from the differences between reference, processed, and anchor versions of the scene. Quality scores obtained from the subjective experiment were used to determine the optimal combination of partial metric values. Five popular fidelity metrics - SSIM, MS-SSIM, IW-SSIM, VIF, and FSIM - were tested. The performance of the proposed approach was then verified in the subjective experiment.
Structured illumination microscopy (SIM) is a recent microscopy technique that enables one to go beyond the diffraction limit using patterned illumination. The high frequency information is encoded through aliasing into the observed image. By acquiring multiple images with different illumination patterns aliased components can be separated and a highresolution image reconstructed. Here we investigate image processing methods that perform the task of high-resolution image reconstruction, namely square-law detection, scaled subtraction, super-resolution SIM (SR-SIM), and Bayesian estimation. The optical sectioning and lateral resolution improvement abilities of these algorithms were tested under various noise level conditions on simulated data and on fluorescence microscopy images of a pollen grain test sample and of a cultured cell stained for the actin cytoskeleton. In order to compare the performance of the algorithms, the following objective criteria were evaluated: Signal to Noise Ratio (SNR), Signal to Background Ratio (SBR), circular average of the power spectral density and the S3 sharpness index. The results show that SR-SIM and Bayesian estimation combine illumination patterned images more effectively and provide better lateral resolution in exchange for more complex image processing. SR-SIM requires one to precisely shift the separated spectral components to their proper positions in reciprocal space. High noise levels in the raw data can cause inaccuracies in the shifts of the spectral components which degrade the super-resolved image. Bayesian estimation has proven to be more robust to changes in noise level and illumination pattern frequency.
The aim of this paper is twofold. In the first part of the paper we present results of subjective quality assessment based comparison of stereoscopic technologies in various configurations. Subjective assessment has been done on a limited set of observers while using a database of stereoscopic test videos of various source types. There is also comparison of results obtained with the same stereoscopic content from the two cooperating test laboratories. The results can be used to address different aspects of viewing experience, especially comparing passive and active stereoscopic display technologies. The second part of the paper is focused on preliminary experimental results analyzing the vergence-accommodation conflict present in current stereoscopic systems. Simultaneous measurement of the vergence and accommodation has been done with observers viewing a real scene and its stereoscopic reproduction.
This paper deals with the criteria definition of image quality in astronomy and their comparison with common
multimedia approaches. Astronomical images have typical specific properties - high grayscale bit depth, size,
high noise occurrence, sensitivity to point spread function deformation and special processing algorithms. They
belong to the class of scientific images as well as medical or similar. Their processing and compression is quite
different from the classical approach of multimedia image processing. The new compression algorithm based
on JPEG2000 is selected as a distortion source in this paper. Selected image quality criteria (multimedia and
optimized for astronomical images) are tested on the set of images from the DEIMOS image database with
miscellaneous level of the thermally generated CCD noise. The deformation of the point spread function (PSF)
is also measured for chosen compression approach.
In this paper we present current progress in the project DEIMOS (Database of Images: Open Source). The DEIMOS
database is an open-source database of images and videos for testing, verification and comparison of various image
and/or video processing techniques. This paper presents additionally measured camera data available with high dynamic
range image content and description of stereoscopic content available in the database. The database of stereoscopic
images with various parameters in acquisition and image processing is intended for testing and optimization of metrics
for objective image quality assessment. An example experiment of perceived image quality assessment depending on
particular testing condition in stereoscopic image acquisition is presented. The database will be gradually annotated with
mean opinion scores of perceived image quality from human observes for each testing condition.
This paper presents a study of possible utilization of digital single-lens reflex (DSLR) cameras in astronomy.
The DSLRs have a great advantage over the professional equipments in better cost efficiency with comparable
usability for selected purposes. The quality of electro-optical system in the DSLR camera determines the area
where it can be used with acceptable precision. At first a set of important camera parameters for astronomical
utilization is introduced in the paper. Color filter array (CFA) structure, demosaicing algorithm, image sensor
spectral properties, noise and transfer characteristics are the parameters that belong among the very important
ones and these are further analyzed in the paper. Compression of astronomical images using the KLT approach
is also described below. The potential impact of these parameters on position and photometric measurement
is presented based on the analysis and measurements with the wide-angle lens. The prospective utilization of
consumer DSLR camera as a substitute for expensive devices is discussed.
Efficient development of image processing techniques requires a database of suitable test images for verification of the
performance, optimization and other related purposes. In this paper, the DEIMOS, an open-source database, is described
including its structure and interface. There is a selected application example on high dynamic range content to illustrate
the database features. This HDR image database contains a variety of natural scenes captured with a digital single-lens
reflex camera (DSLR) under different conditions. The important capture parameters as well as the important
characteristics of the camera are part of the database to ensure that the creation of each image is well documented. The
DEIMOS database is created gradually step-by-step based upon the contributions of team members.
Development, testing, verification and comparison of various image processing techniques require suitable database of
test images. In this paper the DEIMOS, an open-source database, is introduced. This database is aiming various
application fields of image processing such as enhancement, compression and reconstruction. At first requirements on
different image classes are defined in respect to the specific area of application. The paper also describes basic
parameters of the database. There are selected application examples to illustrate extensive database content. The
DEIMOS database is created gradually step-by-step based upon the contributions of team members.
Image capturing by CCD/CMOS cameras is encumbered with two fundamental perturbing influences. Time invariant blurring
(image convolution with fixed kernel) and time variant noises. Both of these influences can be successfully eliminated
by the iterative detection networks (IDNs), that effectively and suboptimally (iteratively) solve 2D MAP criterion through
the image decomposition to the small areas. Preferably to the individual pixel level, if this allows the noise distribution (statistically
independent noise). Nevertheless, this task is so extremely numerically exacting and therefore the contemporary
IDNs are limited only for restorations of dichromatic images.
The IDNs are composed of certain, as simple as possible, statistical devices (SISO modules) and can be separated into two
basic groups with variable topology (exactly matched to the blurring kernel) and with fixed topology, same for all possible
kernels. The paper deals with second group of IDNs, concretely with IDNs whose SISO modules are concatenated in
three directions (horizontal, vertical and diagonal). Advantages of such ordering rests in the application flexibility (can be
comfortable applied to many irregular cores) and also in the low exigencies to number of memory devices it the IDN. The
mentioned IDN type will be implemented in the two different variants suppressing defocusing in the lens of CCD/CMOS
sensing system and will be verified in the sphere of a dichromatic 2D barcode detection.
The paper deals with elimination of defocusing and thermal noise out of black & white pictures captured by a
CCD/CMOS camera with imperfectly adjusted lens. For purposes of image recovery we can use the MAP criterion based
iterative detection network (IDN) containing a number of mutually concatenated functional blocks so-called soft
inversions (SISOs). This cellular structure makes IDN suboptimal but also numerically very simple and practically
applicable in contrast to an unviable optimal (single-stage) MAP detector. Firstly we focus closer on SISO entities and
consequently on the creation of entire IDN, specifically the so-called distributed IDN marginalizing at the symbol level.
In the end, image reconstruction example will be presented (using this type of IDN) along with its performance
characteristics (BER curves) for various levels of defocus.
The paper deals with elimination of blurring caused by the object moving and thermal noise in black & white pictures captured by a CCD/CMOS camera. This problem can be also interpreted like image passage through some kind of ISI channel with specific 2D impulse response. Hence for purposes of image recovery we can use the MAP criterion based iterative detection network (IDN) containing a number of mutually concatenated functional blocks so-called soft inversions (SISOs). This cellular structure makes IDN suboptimal but also numerically very simple and practically applicable in contrast to an unviable optimal (single-stage) MAP detector. Firstly we focus closer to parameters determination of the image blurring hypothetical model (misrepresenting ISI channel). Consequently we are going to deal with the SISO entities and the synthesis of entire IDN, specifically the synthesis of so-called distributed IDN marginalizing at the symbol level because this structure presents the best solution for the mentioned issue. At the end, the image reconstruction example will be presented (using this type of IDN).
The subjective image quality is an important issue in all multimedia imaging systems with a significant impact onto QoS
(Quality of Service). For long time the image fidelity criterion was widely applied in technical systems esp. in both
television and image source compression fields but the optimization of subjective perception quality and fidelity
approach (such as the minimum of MSE) are very different. The paper presents an experimental testing of three different
digital techniques for the subjective image quality enhancement - color saturation, edge enhancement, denoising
operators and noise addition - well known from both the digital photography and video. The evaluation has been done
for extensive operator parameterization and the results are summarized and discussed. It has been demonstrated that
there are relevant types of image corrections improving to some extent the subjective perception of the image. The above
mentioned techniques have been tested for five image tests with significantly different image characteristics (fine details,
large saturated color areas, high color contrast, easy-to-remember colors etc.). The experimental results show the way to
optimized use of image enhancing operators. Finally the concept of impressiveness as a new possible expression of
subjective quality improvement is presented and discussed.
The subjective image quality seems to be one of crucial parameters in modern multimedia systems. The perception of observer is a final issue to be followed and technical parameters of the system are the issues of second order. Therefore the traditional approach of "fidelity" would be better consequently replaced by the multimedia term the subjective image perceived quality or "goodliness". It can be shown that some distortions and/or artifacts can be perceived as pleasant and the goodliness will be increased when the distortion level is increased. At the same time the fidelity will drop down. Based upon more than four years of research experience the paper discusses various impacts of modem multimedia technology on the subjective quality of image. The main attention is focused on the image compression techniques and standards. The nature of distortions and artifacts is demonstrated on selected examples of image compression standards (fractals, DIVX, VP6 etc.). Finally the relevant image quality parameters are listed and analyzed for the area of imaging security systems.
The submitted paper is devoted to a description of relevant experience with an implementation of optical JTC (Joint Transform Correlation) processing technique in two selected security applications - fingerprint and face recognition. It summarizes a long time testing of the above mentioned technique under various conditions and effects appearing frequently in real applications. The JTC configuration is a very well known optical scheme for a 2D correlation calculation that is widely used for identification and classification purposes in image databases. The optical hardware provides a fast and massively parallel performance with large computational power required by the 2D image correlation. The performance of a real setup exhibits some shortcomings caused by expected initial distortions and artifacts in the image. The numerous distortions have been tested such as zooming, deformation etc. relevant for real samples of fingerprints and faces and some results are summarized here and presented in comprehensive diagrams.
The submitted paper is describes a relevant experience in an introduction of photonic information processing techniques into the curricula of MSc course subject Image Processing and Photonics and PhD course subject Selected Parts from Photonics. The photonic information processing systems offer extensive computational power because of several advantages: the information carrier - photon - is the fastest one, massively parallel access and computation, some mathematical operations performed by physical effects (2D convolution, 2D Fourier transform).
The paper is devoted to an education of Photonics at the Dept. of Telecommunications, Faculty of Electrical Engineering, at the University of Zilina. Originated from the university historical development the photonic subjects are implemented in two basic areas: Telecommunication Technology and Radiocommunication Technology. From the school year 1994/95 the new subject Photonics has been taught and it has attracted numerous students. The subject is focused on both physical principles and system application. The relevant parts can be listed as: interaction photon - matter, photonic receivers and transmitters, modulation and demodulation in Photonics, photonic networks - narrowband and wideband, photonic switches, image sensors and displays. The education of Photonics has been supported by research activities in the field of applied photonic system for signal (data) transmission and selected results have been implemented into the subject structure. The paper listed a detailed content of the subject in two fields: lectures and experimental laboratory exercises. As an integral part of the course we plan to implement selected experiments from the area of 2D photonic (image) processing and to expand the imaging photonic part.
The article is devoted to the development of technical university course in photonics. The work has been done and the results are two grants from the Czech Ministry of Education and it has covered all three parts of study - BSc course, MSc course and PhD course. The structure of existing subjects was overviewed and the new system has been created. A different approach has been implemented in the PhD course where the extensive participation of students in R and D has been essential.
A 2D correlation of images is one of very efficient methods used in both identification and classification area of image processing. Numerical evaluation of 2D is computationally highly demanding and therefore the optical methods are interested because of parallel and fast performance. The JTC (Joint Fourier Transform) is a well known optical technique for an evaluation of 2D correlation. The paper deals with practical problems of JTC technique implementation-- available SLMs, image sensors and modifications of original optical system. Finally some possible applications in transport are discussed.
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