- 标题
- 摘要
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- 实验方案
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Functional Diversity in the Retina Improves the Population Code
摘要： Within a given brain region, individual neurons exhibit a wide variety of different feature selectivities. Here, we investigated the impact of this extensive functional diversity on the population neural code. Our approach was to build optimal decoders to discriminate among stimuli using the spiking output of a real, measured neural population and compare its performance against a matched, homogeneous neural population with the same number of cells and spikes. Analyzing large populations of retinal ganglion cells, we found that the real, heterogeneous population can yield a discrimination error lower than the homogeneous population by several orders of magnitude and consequently can encode much more visual information. This effect increases with population size and with graded degrees of heterogeneity. We complemented these results with an analysis of coding based on the Chernoff distance, as well as derivations of inequalities on coding in certain limits, from which we can conclude that the beneficial effect of heterogeneity occurs over a broad set of conditions. Together, our results indicate that the presence of functional diversity in neural populations can enhance their coding fidelity appreciably. A noteworthy outcome of our study is that this effect can be extremely strong and should be taken into account when investigating design principles for neural circuits.
关键词： retina,neural coding,discrimination error,mutual information,functional diversity,Chernoff distance,population code,heterogeneity
更新于2025-09-23 15:23:52
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Multi-Focus Image Fusion Based on Multiple Directional LOTs
摘要： This letter proposes an image fusion method which adopts a union of multiple directional lapped orthogonal transforms (DirLOTs). DirLOTs are used to generate symmetric orthogonal discrete wavelet transforms and then to construct a union of unitary transforms as a redundant dictionary with a multiple directional property. The multiple DirLOTs can overcome a disadvantage of separable wavelets to represent images which contain slant textures and edges. We analyse the characteristic of local luminance contrast, and propose a fusion rule based on interscale relation of wavelet coefficients. Relying on the above, a novel image fusion method is proposed. Some experimental results show that the proposed method is able to significantly improve the fusion performance from those with the conventional discrete wavelet transforms.
关键词： image fusion,multiple DirLOTs,mutual information
更新于2025-09-23 15:22:29
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Rectangular-Normalized Superpixel Entropy Index for Image Quality Assessment
摘要： Image quality assessment (IQA) is a fundamental problem in image processing that aims to measure the objective quality of a distorted image. Traditional full-reference (FR) IQA methods use fixed-size sliding windows to obtain structure information but ignore the variable spatial configuration information. In order to better measure the multi-scale objects, we propose a novel IQA method, named RSEI, based on the perspective of the variable receptive field and information entropy. First, we find that consistence relationship exists between the information fidelity and human visual of individuals. Thus, we reproduce the human visual system (HVS) to semantically divide the image into multiple patches via rectangular-normalized superpixel segmentation. Then the weights of each image patches are adaptively calculated via their information volume. We verify the effectiveness of RSEI by applying it to data from the TID2008 database and denoise algorithms. Experiments show that RSEI outperforms some state-of-the-art IQA algorithms, including visual information fidelity (VIF) and weighted average deep image quality measure (WaDIQaM).
关键词： image quality assessment,superpixel segmentation,mutual information
更新于2025-09-23 15:22:29
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Harvesting correlations from thermal and squeezed coherent states
摘要： We study the harvesting of entanglement and mutual information by Unruh-DeWitt particle detectors from thermal and squeezed coherent field states. We prove (for arbitrary spatial dimensions, switching profiles and detector smearings) that while the entanglement harvesting ability of detectors decreases monotonically with the field temperature T, harvested mutual information grows linearly with T. We also show that entanglement harvesting from a general squeezed coherent state is independent of the coherent amplitude, but depends strongly on the squeezing amplitude. Moreover, we find that highly squeezed states (i) allow for detectors to harvest much more entanglement than from the vacuum, and (ii) ensure that the entanglement harvested does not decay with their spatial separation. Finally, we analyze the spatial inhomogeneity of squeezed states and its influence on harvesting, and investigate how much entanglement one can actually extract from squeezed states when the squeezing is bandlimited.
关键词： Unruh-DeWitt detectors,thermal states,entanglement harvesting,quantum field theory,squeezed coherent states,mutual information
更新于2025-09-23 15:22:29
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Automatic Registration of INSAT-3D Daily Images Using Mutual Information and Stochastic Optimization Technique
摘要： An automatic image registration approach is presented here can be used to register daily images of Indian geostationary satellite system INSAT-3D acquired every 30 min’ interval without use of any ground control points (GCPs). There is always a pressing need to register meteorological images that are acquired over earth from geostationary platforms every 15–30 min, covering almost one-third of the earth. Weather forecast activities include derivation of atmospheric motion vectors, which demand immediate processing of such images to a reasonable accuracy in terms of its relative location accuracy. Generally followed approaches make use of image navigation models and GCPs drawn from known landmarks in land ocean boundaries and correlate image features before estimating a transform to warp the current acquisition to a known geometry. However, the hierarchical (coarse to ?ne) approach explained here makes use of intensity based Mutual Information as a similarity measure from a population of pixels selected randomly and uses stochastic gradient descent optimizer to estimate an af?ne transform between registering image pair, delivers satisfactory results.
关键词： Mutual information,Stochastic optimization,INSAT-3D,Image registration
更新于2025-09-23 15:21:21
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A new filter for dimensionality reduction and classification of hyperspectral images using GLCM features and mutual information
摘要： Dimensionality reduction is an important preprocessing step of the hyperspectral images classification (HSI), it is inevitable task. Some methods use feature selection or extraction algorithms based on spectral and spatial information. In this paper, we introduce a new methodology for dimensionality reduction and classification of HSI taking into account both spectral and spatial information based on mutual information. We characterise the spatial information by the texture features extracted from the grey level cooccurrence matrix (GLCM); we use Homogeneity, Contrast, Correlation and Energy. For classification, we use support vector machine (SVM). The experiments are performed on three well-known hyperspectral benchmark datasets. The proposed algorithm is compared with the state of the art methods. The obtained results of this fusion show that our method outperforms the other approaches by increasing the classification accuracy in a good timing. This method may be improved for more performance.
关键词： hyperspectral images,spectral and spatial features,classification,SVM,mutual information,GLCM,grey level cooccurrence matrix,support vector machine
更新于2025-09-23 15:21:21
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Gradation of diabetic retinopathy on reconstructed image using compressed sensing
摘要： This study explores neovascularisation and lesion detection in an integrated framework for gradation in diabetic retinopathy (DR). Imaging is assumed to be done from sub-sample measurements following compressed sensing. Blind estimation of the scale of the matched filter (MF) followed by fuzzy entropy maximisation is done for extraction and classification of the thick and the thin vessels. Mutual information (MI) between vessel density and tortuosity of the thin vessel class is maximised in two dimensions (2D) for neovascularisation detection. For lesion detection, MI between the maximum MF response and the maximum Laplacian of Gaussian filter response is jointly maximised in 2D. The outcomes are then combined in a common platform for gradation in DR. Simulation results demonstrate that 95% images of each of DRIVE, STARE and DIARETDB1 databases and 94% images of MESSIDOR database are correctly graded by the proposed method when 80% measurement space is considered.
关键词： compressed sensing,lesion detection,diabetic retinopathy,fuzzy entropy,mutual information,neovascularisation
更新于2025-09-23 15:21:21
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[IEEE 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall) - Xiamen, China (2019.12.17-2019.12.20)] 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall) - Dual Polarization (TE and TM) Terahertz Spoof Surface Plasmon Polaritons Enabled by Metasurface
摘要： The FEC limit paradigm is the prevalent practice for designing optical communication systems to attain a certain bit error rate (BER) without forward error correction (FEC). This practice assumes that there is an FEC code that will reduce the BER after decoding to the desired level. In this paper, we challenge this practice and show that the concept of a channel-independent FEC limit is invalid for soft-decision bit-wise decoding. It is shown that for low code rates and high-order modulation formats, the use of the soft-decision FEC limit paradigm can underestimate the spectral efficiencies by up to 20%. A better predictor for the BER after decoding is the generalized mutual information, which is shown to give consistent post-FEC BER predictions across different channel conditions and modulation formats. Extensive optical full-field simulations and experiments are carried out in both the linear and nonlinear transmission regimes to confirm the theoretical analysis.
关键词： forward error correction,soft-decision decoding,generalized mutual information,Bit error rate,mutual information
更新于2025-09-23 15:19:57
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FibAR: Embedding Optical Fibers in 3D Printed Objects for Active Markers in Dynamic Projection Mapping
摘要： We experimentally investigate mutual information and generalized mutual information for coherent optical transmission systems. The impact of the assumed channel distribution on the achievable rate is investigated for distributions in up to four dimensions. Single channel and wavelength-division multiplexing (WDM) transmission over transmission links with and without inline dispersion compensation are studied. We show that for conventional WDM systems without inline dispersion compensation, a circularly symmetric complex Gaussian distribution is a good approximation of the channel. For other channels, such as with inline dispersion compensation, this is no longer true and gains in the achievable information rate are obtained by considering more sophisticated four-dimensional (4D) distributions. We also show that for nonlinear channels, gains in the achievable information rate can also be achieved by estimating the mean values of the received constellation in four dimensions. The highest gain for such channels is seen for a 4D correlated Gaussian distribution.
关键词： mutual Information,digital communication,fiber nonlinear optics,optical fiber communication,Channel models
更新于2025-09-23 15:19:57
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Image Fusion Based on Kernel Estimation and Data Envelopment Analysis
摘要： This paper reports the improvement of the image quality during the fusion of remote sensing images by minimizing a novel energy function. First, by introducing a gradient constraint term in the energy function, the spatial information of the panchromatic image is transferred to the fused results. Second, the spectral information of the multispectral image is preserved by importing a kernel function to the data fitting term in the energy function. Finally, an objective parameter selection method based on data envelopment analysis (DEA) is proposed to integrate state-of-the-art image quality metrics. Visual perception measurement and selected fusion metrics are employed to evaluate the fusion performance. Experimental results show that the proposed method outperforms other established image fusion techniques.
关键词： Data envelopment analysis,mutual information.,image fusion
更新于2025-09-19 17:15:36