Many methods can be used to construct geographical cellular automata (CA) models of urban land use, but most do not adequately capture spatial heterogeneity in urban dynamics. Spatial regression is ...particularly appropriate to address the problem to reproduce urban patterns. To examine the advantages and disadvantages of spatial regression, we compare a spatial lag CA model (SLM-CA), a spatial error CA model (SEM-CA) and a geographically-weighted regression CA model (GWR-CA) by simulating urban growth at Nanjing, China. Each CA model is calibrated from 1995 to 2005 and validated from 2005 to 2015. Among these, SLM and SEM are spatial autoregressive (SAR) models that consider spatial autocorrelation of urban growth and yield highly similar land transition probability maps. Both SAR-CA and GWR-CA accurately reproduce urban growth at Nanjing during the calibration and validation phases, yielding overall accuracies (OAs) exceeding 94% and 85%, respectively. SAR-CA is superior in simulating urban growth when measured by OA and figure-of-merit (FOM) while GWR-CA is superior regarding the ability to address spatial heterogeneity. A concentric ring buffer-based assessment shows OA valleys that correspond to FOM peaks, where the ranges of valleys and peaks indicate the areas with active urban development. By comparison, SAR-CA captures more newly-urbanized patches in highly-dense urban areas and shows better performance in terms of simulation accuracy; whereas, GWR-CA captures more in the suburbs and shows better ability to address spatial heterogeneity. Our results demonstrate that spatial regression can help produce accurate simulations of urban dynamics featured by spatial heterogeneity, either implicitly or explicitly. Our work should help select appropriate CA models of urban growth in different terrain and socioeconomic contexts.
•We compared SLM-CA, SEM-CA and GWR-CA by simulating urban growth at Nanjing.•SLM and SEM are spatial autoregressive (SAR) models considering spatial autocorrelation.•SAR-CA shows advantages over GWR-CA in terms of OA and FOM.•SAR-CA captures more newly urbanized cells in the rapidly urbanizing areas.•GWR-CA captures more newly urbanized cells in the suburbs and better addresses spatial heterogeneity.
The visibility and analyzability of MRI and CT images have a great impact on the diagnosis of medical diseases. Therefore, for low-quality MRI and CT images, it is necessary to effectively improve ...the contrast while suppressing the noise. In this paper, we propose an enhancement and denoising strategy for low-quality medical images based on the sequence decomposition Retinex model and the inverse haze removal approach. To be specific, we first estimate the smoothed illumination and de-noised reflectance in a successive sequence. Then, we apply a color inversion from 0–255 to the estimated illumination, and introduce a haze removal approach based on the dark channel prior to adjust the inverted illumination. Finally, the enhanced image is generated by combining the adjusted illumination and the de-noised reflectance. As a result, improved visibility is obtained from the processed images and inefficient or excessive enhancement is avoided. To verify the reliability of the proposed method, we perform qualitative and quantitative evaluation on five MRI datasets and one CT dataset. Experimental results demonstrate that the proposed method strikes a splendid balance between enhancement and denoising, providing performance superior to that of several state-of-the-art methods.
Graphical abstract
In optical interferometry methods, a challenging problem is how to preserve the edges of all fringes perfectly whilst reducing speckle noise effectively. Directivity is an important characteristic of ...optical interferometry fringes, and it plays an extremely important role in directing the filtering process. Bilateral filtering is a well-known filtering method for edge-preserving in image processing. In this paper, we propose an oriented bilateral filtering method with special application for optical interferometry fringes by incorporating a directional mask to original bilateral filtering method. We test our oriented bilateral filtering method by applying it to four computer-simulated and one experimentally obtained ESPI fringe patterns, respectively, and compare it with the original bilateral filtering method and the tangent least-squares fitting filtering method. The experimental results demonstrate that the proposed method performs impressively in speckle reduction and fringe edge preservation.
Abstract
Automatic photoelastic method focuses on the recognition of stress field. RGB photoelastic method has the advantages of low condition requirements and accurate low-level fringe recognition, ...but it is easy to be disturbed by image noise, color repetition and other factors, resulting in recognition errors. In this study, the combination of gradient-square inversion and RGB photoelastic technology can not only effectively eliminate the error points introduced by color repetition, but also greatly reduce the scope of look-up table, shorten the calculation time and quickly analyze the stress field. The effectiveness of the proposed RGB photoelastic method based on gradient-square inversion correction is verified by photoelastic experiments.
Land use change affected by wide ranges of human activities is a key driver of global climate change. In the last three decades, China has experienced unprecedented land use change accompanied by ...increasing environmental problems. There is a pressing need to project and analyze long-term land use scenarios that are critical for land use planning and policymaking. Using GlobeLand30 data, we examined China's land use change from 2000 to 2010, and developed a novel LandCA model for scenario projections from 2020 to 2050. The observed and projected land use change (2000–2050) was analyzed in terms of the interval, category, and transition levels. Our findings show that land Exchange intensity is more than 3 times greater than land Quantity intensity from 2000 to 2050, and the overall rate of land use change will decelerate from 2010 to 2050. During 2000–2010, the loss of built-up land to other categories was 12.7% while the gain was 32.5%, with a growth rate 3.4 times larger than that during 2010–2050. The total amount of cultivated land continuously decreases but will not violate the Chinese “Cultivated Land Red-Line Restriction” by 2050. We speculate that the government's goal of 26% forest cover by 2050 may not be achieved, as a result of strict land use policies preventing the transformation from cultivated land to forests. This study contributes to new evaluations of long-term land use change in China for the government to adjust policies and regulations for sustainable development.
•We modeled China's land use change during 2000–2050.•Exchange intensity is more than 3 times of the quantity intensity during 2000–2050.•The total cultivated area by 2050 will not violate the government's restriction.•The goal of 26% forest coverage by 2050 may not be achieved; and.•The built-up area growth rate during 2000–2010 is 3.4 times that from 2010 to 2050.
•The security level of our encryption framework can be significantly improved by increasing the number of Shearlet coefficient sub-images.•The proposed encryption framework can flexibly select ...scrambling algorithm to permutation and diffusion the pixels in sub-images.•The proposed encryption framework can flexibly select reversible synthesize methods to combined the scrambled sub-images into one.
The security of medical image data for transmission and storage is a critical issue. Texture information of medical images is important for diagnosis. Since Shearlets is particularly effective in characterizing texture information, in this paper, we propose a generalized optical encryption framework based on Shearlets and double random phase encoding (DRPE) especially for medical images. In the proposed encryption framework, the secret medical image is first decomposed into n sub-images with shearlet transform. Then, the sub-images or pixel positions are shuffled by scrambling algorithm. Subsequently, the shuffled sub-images are synthesized into one image. Finally, the synthesized image is encoded with DRPE. The security level of the proposed encryption framework can be improved by changing the parameters of shearlet transform and selecting different methods for scrambling pixels and synthesizing multiple images to single image. Extensive simulation results have shown the performance of the proposed optical encryption framework. The proposed encryption framework can be improved along with novelty scrambling method and reversible synthesize methods.
Abstract The laminated and sandwich composite structural batteries can efficiently store energy and bear loading while effectively saving mass and volume. To prepare these two types of composite ...structure batteries, an experimental platform of vacuum-assisted resin transfer process was constructed, and the preparation processes of laminated and sandwich plates were studied. The comparative analysis of the open-circuit voltage with SOC at different temperatures demonstrated the stability and reliability of the preparation processes for composite structure batteries.
Generally speaking, it is the essential core of image filtering to keep the texture features better while denoising the image. To some extent, optical coherence tomography retina images have speckle ...noise, which masks the texture features of the image, and thus causes misjudgment to the doctor’s diagnosis. In this paper, we first propose a cluster-based filtering framework for removing speckles with structural protection in OCT images. The overall process can be divided into preprocessing, structure extraction and structure denoising. First, in the preprocessing stage, we propose to use the shearlet (SHT) method for preliminary filtering and combine block search and matching to achieve structure protection. Then in the structure extraction stage, we propose to use the relative total variation algorithm to achieve structure extraction, combined with fuzzy C-means Clustering filters out the background noise to obtain the structure mask of the image. Finally, in the structure denoising stage, we propose a new variational Block matching 3D (BM3D)-L
2
method, and the structure of the image and the noise are described in BM3D space and L
2
space, respectively. By assigning appropriate values to the parameters, image noise can be better eliminated, and the structural texture of the image can be protected. We test the proposed method on seven large noisy OCT images, which include five human retinal OCT images and two mouse optic nerve OCT images. In addition, we also compare it with SHT, BM3D, TV-SHT and TV-BM3D methods, which were proved to be effective in denoising. The performances of these methods are quantitatively evaluated in terms of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and the averaged equivalent number of looks (ENL) at the aspects of speckle reduction and structure texture protection. Vast experiments show that our proposed method can effectively reduce speckle noise in OCT images, protect important structural information and improve image quality. Here, we believe that our method will improve image segmentation, medical diagnosis, and can use this as training samples to improve the accuracy of machine learning.
In the paper, we propose a batch fringe extraction method for the single FPP fringe pattern based on a triple serial and parallel convolution neural network. The proposed network is a combination of ...three deep convolution neural networks in a serial and parallel way. We train the network by pairs of the original FPP fringe patterns and the corresponding fringe components. When the network is trained successfully, the fringe component can be obtained directly by feeding the original FPP fringe pattern into the trained network. Based on the extracted fringe component, we get the desired phase. We test the proposed method on many FPP fringe patterns and compare them with four reference methods including the Fourier transform, Shearlet transform, bi-dimensional empirical mode decomposition, and variational image decomposition methods. We also evaluate the performances with three quantitative metrics and four visual presentations. The experiment results show that the proposed method can extract the fringe component more accurately than the four reference methods. Besides, the proposed method can adaptively process different FPP fringe patterns in batch without any parameter fine-tuning. Additionally, the proposed method has been applied in a real dynamic measurement of a leaf in continuous dehydration successfully.
In the existing cryptosystems such as double random phase encoding (DRPE)-based, the input image is usually modulated with the random phase mask (RPM) by multiplication. Based on the existing DRPE ...cryptosystems, in this paper, we propose a novel asymmetric cryptosystem based on the QZ modulation. We introduce the QZ algorithm to modulate the plain image and the random phase mask for the first time. In our cryptosystem, we take the input image and RPM as two inputs of the QZ algorithm. The outputs of the QZ algorithm include four parts: two upper quasitriangular matrices and two unitary matrices. Then the upper quasitriangular matrice corresponding to the plain image is encoded in the optical transform domain to obtain the cipher image. Meanwhile, the two unitary matrices are regarded as private keys only for decryption. Therefore, our QZ-based cryptosystem is asymmetric. Furthermore, the two RPMs are not required in the whole decryption process. The numerical results have shown the feasibility, security, and superiority of our cryptosystem. The proposed QZ-based modulation method can be applied to any other optical cryptosystem, and the encryption for color normal or medical images.
