scholarly journals Pansharpening of WorldView-2 Data via Graph Regularized Sparse Coding and Adaptive Coupled Dictionary

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3586
Author(s):  
Wenqing Wang ◽  
Han Liu ◽  
Guo Xie
Keyword(s):  
High Resolution ◽  
Sparse Representation ◽  
Sparse Coding ◽  
Spectral Response ◽  
Objective Evaluation ◽  
Coefficient Matrix ◽  
Image Patch ◽  
Subjective Analysis ◽  
High Resolution Image ◽  
Sparse Coefficient

The spectral mismatch between a multispectral (MS) image and its corresponding panchromatic (PAN) image affects the pansharpening quality, especially for WorldView-2 data. To handle this problem, a pansharpening method based on graph regularized sparse coding (GRSC) and adaptive coupled dictionary is proposed in this paper. Firstly, the pansharpening process is divided into three tasks according to the degree of correlation among the MS and PAN channels and the relative spectral response of WorldView-2 sensor. Then, for each task, the image patch set from the MS channels is clustered into several subsets, and the sparse representation of each subset is estimated through the GRSC algorithm. Besides, an adaptive coupled dictionary pair for each task is constructed to effectively represent the subsets. Finally, the high-resolution image subsets for each task are obtained by multiplying the estimated sparse coefficient matrix by the corresponding dictionary. A variety of experiments are conducted on the WorldView-2 data, and the experimental results demonstrate that the proposed method achieves better performance than the existing pansharpening algorithms in both subjective analysis and objective evaluation.

scholarly journals Multisensor Fusion of Landsat Images for High-Resolution Thermal Infrared Images Using Sparse Representations

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Hong Sung Jin ◽  
Dongyeob Han
Keyword(s):  
High Resolution ◽  
Sparse Representation ◽  
Spatial Resolution ◽  
Land Surface ◽  
Spectral Response ◽  
Thermal Infrared ◽  
Environmental Research ◽  
Infrared Images ◽  
Thermal Infrared Images ◽  
Thermal Band

Land surface temperature (LST) is an important parameter in the analysis of climate and human-environment interactions. Landsat Earth observation satellite data including a thermal band have been used for environmental research and applications; however, the spatial resolution of this thermal band is relatively low. This study investigates an efficient method of fusing Landsat panchromatic and thermal infrared images using a sparse representation (SR) technique. The application of SR is used for the estimation of missing details of the available thermal infrared (TIR) image to enhance its spatial features. First, we propose a method of building a proper dictionary considering the spatial resolution of the original thermal image. Second, a sparse representation relation between low- and high-resolution images is constructed in terms of the Landsat spectral response. We then compare the fused images created with different sampling factors and patch sizes. The results of both qualitative and quantitative evaluation show that the proposed method improves spatial resolution and preserves the thermal properties of basic LST data for use with environmental problems.

Image Restoration via Group l2,1 Norm-Based Structural Sparse Representation

2017 ◽  
Vol 32 (04) ◽  
pp. 1854008 ◽  
Author(s):  
Kai Song Zhang ◽  
Luo Zhong ◽  
Xuan Ya Zhang
Keyword(s):  
Image Restoration ◽  
Sparse Representation ◽  
Sparse Coding ◽  
Structural Information ◽  
Signal To Noise Ratio ◽  
Coefficient Matrix ◽  
Optimization Approach ◽  
Signal To Noise ◽  
Nonlinear Features ◽  
Characteristics Of Image

Sparse representation has recently been extensively studied in the field of image restoration. Many sparsity-based approaches enforce sparse coding on patches with certain constraints. However, extracting structural information is a challenging task in the field image restoration. Motivated by the fact that structured sparse representation (SSR) method can capture the inner characteristics of image structures, which helps in finding sparse representations of nonlinear features or patterns, we propose the SSR approach for image restoration. Specifically, a generalized model is developed using structured restraint, namely, the group [Formula: see text]-norm of the coefficient matrix is introduced in the traditional sparse representation with respect to minimizing the differences within classes and maximizing the differences between classes for sparse representation, and its applications with image restoration are also explored. The sparse coefficients of SSR are obtained through iterative optimization approach. Experimental results have shown that the proposed SSR technique can significantly deliver the reconstructed images with high quality, which manifest the effectiveness of our approach in both peak signal-to-noise ratio performance and visual perception.

scholarly journals A New Integrated Approach Based on the Iterative Super-Resolution Algorithm and Expectation Maximization for Face Hallucination

2020 ◽  
Vol 10 (2) ◽  
pp. 718 ◽  
Author(s):  
K. Lakshminarayanan ◽  
R. Santhana Krishnan ◽  
E. Golden Julie ◽  
Y. Harold Robinson ◽  
Raghvendra Kumar ◽  
...  
Keyword(s):  
High Resolution ◽  
Sparse Representation ◽  
Expectation Maximization ◽  
Super Resolution ◽  
Integrated Approach ◽  
Face Hallucination ◽  
Resolution Image ◽  
High Resolution Image ◽  
Face Images ◽  
Resolution Algorithm

This paper proposed and verified a new integrated approach based on the iterative super-resolution algorithm and expectation-maximization for face hallucination, which is a process of converting a low-resolution face image to a high-resolution image. The current sparse representation for super resolving generic image patches is not suitable for global face images due to its lower accuracy and time-consumption. To solve this, in the new method, training global face sparse representation was used to reconstruct images with misalignment variations after the local geometric co-occurrence matrix. In the testing phase, we proposed a hybrid method, which is a combination of the sparse global representation and the local linear regression using the Expectation Maximization (EM) algorithm. Therefore, this work recovered the high-resolution image of a corresponding low-resolution image. Experimental validation suggested improvement of the overall accuracy of the proposed method with fast identification of high-resolution face images without misalignment.

scholarly journals International Journal of Applied Mathematics and Machine Learning

2021 ◽  
Vol 15 (1) ◽  
pp. 1-29
Author(s):  
Xiuming Sun ◽  
◽  
Weina Wu ◽  
Peng Geng ◽  
Lin Lu ◽  
...  
Keyword(s):  
Image Fusion ◽  
Sparse Representation ◽  
Color Image ◽  
Applied Mathematics ◽  
Objective Evaluation ◽  
Relevant Information ◽  
Computational Mathematics ◽  
Fused Image ◽  
Focus Image ◽  
Sparse Coefficient

In order to achieve the multi-focus image fusion task, a sparse representation method based on quaternion for multi-focus image fusion is proposed in this paper. Firstly, the RGB color information of each pixel in the color image is represented by quaternion based on the relevant knowledge of computational mathematics, and the color image pixel is processed as a whole vector to maintain the relevant information between the three color channels. Secondly, the dictionary represented by quaternion and the sparse coefficient represented by quaternion are obtained by using the our proposed sparse representation model. Thirdly, the coefficient fusion is carried out by using the “max-L1” rule. Finally, the fused sparse coefficient and dictionary are used for image reconstruction to obtain the quaternion fused image, which is then converted into RGB color multi-focus fused image. Our method belongs to computational mathematics, and uses the relevant knowledge in the field of computational mathematics to help us carry out the experiment. The experimental results show that the method has achieved good results in visual quality and objective evaluation.

Radiation Damage, Contrast and Statistics in High Resolution Biological Electron Microscopy

1970 ◽  
Vol 28 ◽  
pp. 260-261
Author(s):  
Robert M. Glaeser
Keyword(s):  
High Resolution ◽  
Particle Flux ◽  
Unit Area ◽  
Signal To Noise ◽  
Resolution Image ◽  
High Resolution Image ◽  
Pass Through ◽  
Counting Statistics ◽  
The Relationship ◽  
Picture Element

It is well known that a large flux of electrons must pass through a specimen in order to obtain a high resolution image while a smaller particle flux is satisfactory for a low resolution image. The minimum particle flux that is required depends upon the contrast in the image and the signal-to-noise (S/N) ratio at which the data are considered acceptable. For a given S/N associated with statistical fluxtuations, the relationship between contrast and “counting statistics” is s131_eqn1, where C = contrast; r2 is the area of a picture element corresponding to the resolution, r; N is the number of electrons incident per unit area of the specimen; f is the fraction of electrons that contribute to formation of the image, relative to the total number of electrons incident upon the object.

Effect of strain on ADF-STEM high-resolution images

1991 ◽  
Vol 49 ◽  
pp. 666-667
Author(s):  
M. Kelly ◽  
D.M. Bird
Keyword(s):  
High Resolution ◽  
Strong Influence ◽  
Intensity Variation ◽  
Dark Field ◽  
Atomic Resolution ◽  
Strain Fields ◽  
High Resolution Image ◽  
Annular Dark Field ◽  
High Resolution Images ◽  
Interesting Alternative

It is well known that strain fields can have a strong influence on the details of HREM images. This, for example, can cause problems in the analysis of edge-on interfaces between lattice mismatched materials. An interesting alternative to conventional HREM imaging has recently been advanced by Pennycook and co-workers where the intensity variation in the annular dark field (ADF) detector is monitored as a STEM probe is scanned across the specimen. It is believed that the observed atomic-resolution contrast is correlated with the intensity of the STEM probe at the atomic sites and the way in which this varies as the probe moves from cell to cell. As well as providing a directly interpretable high-resolution image, there are reasons for believing that ADF-STEM images may be less suseptible to strain than conventional HREM. This is because HREM images arise from the interference of several diffracted beams, each of which is governed by all the excited Bloch waves in the crystal.

Detection of a point defect in a silicon single crystal by high-resolution TEM

1995 ◽  
Vol 53 ◽  
pp. 466-467
Author(s):  
M. Awaji
Keyword(s):  
High Resolution ◽  
Single Crystal ◽  
Point Defect ◽  
Point Defects ◽  
Noise Level ◽  
Dark Field ◽  
Silicon Single Crystal ◽  
High Resolution Image ◽  
Dark Field Imaging ◽  
Field Imaging

It is necessary to improve the resolution, brightness and signal-to-noise ratio(s/n) for the detection and identification of point defects in crystals. In order to observe point defects, multi-beam dark-field imaging is one of the useful methods. Though this method can improve resolution and brightness compared with dark-field imaging by diffuse scattering, the problem of s/n still exists. In order to improve the exposure time due to the low intensity of the dark-field image and the low resolution, we discuss in this paper the bright-field high-resolution image and the corresponding subtracted image with reference to a changing noise level, and examine the possibility for in-situ observation, identification and detection of the movement of a point defect produced in the early stage of damage process by high energy electron bombardment.The high-resolution image contrast of a silicon single crystal in the [10] orientation containing a triple divacancy cluster is calculated using the Cowley-Moodie dynamical theory and for a changing gaussian noise level. This divacancy model was deduced from experimental results obtained by electron spin resonance. The calculation condition was for the lMeV Berkeley ARM operated at 800KeV.

New method for tree stands parameters determination using high resolution images done by unmanned aerial vehicle

2016 ◽  
Author(s):  
А.С. Алексеев ◽  
А.А. Никифоров ◽  
А.А. Михайлова ◽  
М.Р. Вагизов
Keyword(s):  
High Resolution ◽  
Unmanned Aerial Vehicle ◽  
New Method ◽  
Growth And Yield ◽  
Special Treatment ◽  
Resolution Image ◽  
Growing Stock ◽  
High Resolution Image ◽  
Aerial Vehicle ◽  
Area Unit

В связи со старением информационных материалов о состоянии лесов существует потребность в разработке новых методов таксации древостоев, основанных на применении последних научно-технических достижений в области теории структуры и продуктивности древостоев, дистанционных методов изучения лесов, информационных и ГИС технологий. В статье приведены результаты разработки и проверки нового метода определения таксационных характеристик сомкнутых насаждений на основе правила 3/2 и подобных ему правил Хильми и Рейнеке, с одной стороны, и определения числа деревьев на единице площади по снимку сверх высокого разрешения, полученного с помощью БПЛА, с другой. С теоретической точки зрения эта зависимости величин запаса, средней высоты и среднего диаметра от числа стволов на единице площади относятся к классу аллометрических связей, очень часто встречающихся при количественном описании соотношений частей биологических систем разных уровней иерархии, от организмов до экосистем. Параметры аллометрических зависимостей запаса, средних высоты и диаметра от числа стволов на единице площади были определены для основных лесообразующих пород по данным таблиц хода роста нормальных (полных) древостоев с теоретическим показателем степени и затем использованы для расчетов. Число деревьев на единице площади определялось по снимку с разрешением 7,13 см/пиксель, полученному с помощью 4-роторной платформы. Обработка материалов аэрофотосъемки была выполнена в специализированной фотограмметрической системе Agisoft Photoscan. В результате были получены ортофотоплан и цифровая модель поверхности крон деревьев на изучаемую территорию с определением их высот. Для автоматизированной обработки полученных изображений с целью получения значений числа деревьев на единицу площади был создан специализированный скрипт на языке Java. Погрешности определения таксационных характеристик древостоев предлагаемым методом не выше установленных действующими нормативными материалами. Every time there is a demand for new innovative methods of forest resources estimation based on last achievements in theoretical science, remote sensing methods, information and GIS-technologies. In the paper are presented a new method and the results of its application to forest stands growing stock, mean height and diameter determination. The method is based on rule 3/2 and similar Reineke and Hilmy rules, on one hand and high resolution image made by unmanned aerial vehicle, which used for determination of number of trees per area unit, on other. The above rules are well known in quantitative biology as an allometric and widely used for description of different kind of relations in biological systems of various scale: from organisms to ecosystems. Parameters of above allometric relationships between growing stock, mean height and diameter and stems density per area unit was determine on the base of full stock growth and yield tables for main tree species and after used for experimental calculations. The number of trees per area unit was determined after special treatment of high resolution image made by unmanned flying machine. The growing stock, mean height and diameter determined by suggested method was compared with the data of regular forest inventory. Comparison gives positive result and method may be recommended for further development.

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