Hyperspectral Image Denoising Using Low Pass Sparse Banded Filter Matrix for Improved Sparsity Based Classification

Aswathy, C.; Sowmya, V.

doi:10.1016/j.procs.2015.08.005

Cited by 11 publications

(4 citation statements)

References 2 publications

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“…The filter uses sparsit-based strategy to denoise the A and B filter matrices of size (M-1) × (M-1) and (M-1) × M, respectively (Aswathy et al , 2015). The output “o” of filter having input signal “ x ” of length “N” is given by equation (14): …”

Section: Proposed Methodologymentioning

confidence: 99%

Steel truss bridge vibration-based condition monitoring using Savitzky-Golay filter, Hilbert transform, MUSIC and ESPRIT

Sharma

Kumar

Vinayak

et al. 2021

JEDT

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Purpose This study aims to perform the experimental work on a laboratory-constructed steel truss bridge model on which hammer blows are applied for excitation. The vibration response signals of the bridge structure are collected using sensors placed at different nodes. The different damaged states such as no damage, single damage, double damage and triple damage are introduced by cutting members of the bridge. The masked noise with recorded vibration responses generates challenge to properly analyze the health of bridge structure. Design/methodology/approach The analytical modal properties are obtained from finite element model (FEM) developed using SAP2000 software. The response signals are analyzed in frequency domain by power spectrum and in time-frequency domain using spectrogram and Stockwell transform. Various low pass signal-filtering techniques such as variational filter, lowpass sparse banded (AB) filter and Savitzky–Golay (SG) differentiator filter are also applied to refine vibration signals. The proposed methodology further comprises application of Hilbert transform in combination with MUSIC and ESPRIT techniques. Findings The outcomes of SG filter provided the denoised signals using appropriate polynomial degree with proper selected window length. However, certain unwanted frequency peaks still appeared in the outcomes of SG filter. The SG-filtered signals are further analyzed using fused methodology of Hilbert transform-ESPRIT, which shows high accuracy in identifying modal frequencies at different states of the steel truss bridge. Originality/value The sequence of proposed methodology for denoising vibration response signals using SG filter with Hilbert transform-ESPRIT is a novel approach. The outcomes of proposed methodology are much refined and take less computational time.

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Section: Proposed Methodologymentioning

confidence: 99%

Steel truss bridge vibration-based condition monitoring using Savitzky-Golay filter, Hilbert transform, MUSIC and ESPRIT

Sharma

Kumar

Vinayak

et al. 2021

JEDT

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“…This Monte Carlo method is highly time efficient compared to other non-local means (NLM) methods. Authors in [13] use a sparsity-based strategy to effectively restore HSIs by employing low-pass sparse banded filter matrices. However, the main limitations of filteringbased approaches include manual tuning of hyperparameters like window size and patch-size (in NLM-based methods).…”

Section: Related Workmentioning

confidence: 99%

CompoHyDen: Hyperspectral Image Restoration via Nonconvex Componentwise Minimization

Aetesam,

Wasi,

Sharma

2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In this paper, we propose a variational approach for estimating the clean hyperspectral images (HSI) that are corrupted by the combined effect of Gaussian noise, impulse noise, stripes, and deadlines. Successful removal of noise from the corrupted observations is essential for subsequent downstream analyses like classification, spectral unmixing, and target tracking. The main contribution of this work is as follows: Firstly, an objective function is designed for the joint estimation of clean data and impulse corrupted pixels. A rationale is presented for using ℓ0−norm to estimate the exact sparsity induced by impulse noise. Secondly, the problem is reformulated as a multiconvex problem which is solved using proximal projection and alternating minimization. Thirdly, to exploit the spatial-spectral similarity, a non-local and vectorized version of total variation (TV) regularization is proposed to estimate the clean data. Lastly, a study on the parameter sensitivity analysis empirically validates the convergence of the restoration results under different values of the regularization hyperparameters. The experiments conducted over synthetically corrupted and real HSI data obtained from hyperspectral sensors suggest the potential utility of the proposed methodology (CompoHyDen) at a scalable level.

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“…Звичайні метрики, такі як середньоквадратична похибка (mean square error, MSE) або пікове співвідношення сигнал/шум (peak signal to noise ratio, PSNR), все ще широко використовуються для аналізу зображень ДЗ або оцінки ефективності їх обробки [11]. Втім, існує очевидна тенденція застосовувати візуальні показники якості [12][13][14]. Однак кількість робіт, де використовуються показники візуальної якості, все ще є обмеженою [12][13][14][15].…”

Section: вступunclassified

“…Втім, існує очевидна тенденція застосовувати візуальні показники якості [12][13][14]. Однак кількість робіт, де використовуються показники візуальної якості, все ще є обмеженою [12][13][14][15].…”

Section: вступunclassified

Комбінована Метрика Візуальної Якості Зображень Дистанційного Зондування На Основі Нейронної Мережі

Еремеев¹,

Okarma

2020

reks

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The wide distribution of images of remote sensing (RS) of the Earth in various application areas makes it important to ensure the high quality of such images, which is important to identify necessary information. The complexity of the systems and the impact of various physical processes cause a significant number of distortions that lead to image corruption and possible loss of information. The use of processing methods that should reduce the impact of such factors requires control of their work, which uses quantitative indicators of visual quality. The article considers the task of creating a combined visual quality metric based on an artificial neural network (ANN), which provides high accuracy of visual quality assessment and stability of work on the noise characteristic of the RS. The problem of analysis of RS distortions is considered and the approach of using the database of test images TID2013 for verification on typical RS distortions is offered. The analysis of well-known visual quality metrics and their suitability for the estimation of such images is carried out. According to its results, it was determined that the best metrics provide the accuracy of image quality assessment for RS tasks at the level of 0.93 according to Spearman's rank-order correlation coefficient with subjective estimates of the TID2013 image database. The joint application of existing quality metrics allows eliminating the shortcomings of each of them and increasing the overall efficiency, so the article considers the problems and defines the requirements for creating a combined metric involving a neural network. A method of limiting the number of involved quality metrics with the involvement of Lasso regularization is proposed, which allows determining the most informative features (quality metrics) and simplifying the procedure of selection and reduction of their number. A study was conducted on the influence of the metric selection criterion and quantity on the accuracy of the combined metric. The influence of the structure of the neural network, the number of hidden layers, and the number of neurons in them are also analyzed. Based on the obtained results, the best implementation of ANN was selected, which with the involvement of 16 visual quality metrics allows achieving the accuracy of visual quality assessment at 0.97 according to Spearman's correlation with subjective estimates of the TID2013 database.

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Hyperspectral Image Denoising Using Low Pass Sparse Banded Filter Matrix for Improved Sparsity Based Classification

Cited by 11 publications

References 2 publications

Steel truss bridge vibration-based condition monitoring using Savitzky-Golay filter, Hilbert transform, MUSIC and ESPRIT

Steel truss bridge vibration-based condition monitoring using Savitzky-Golay filter, Hilbert transform, MUSIC and ESPRIT

CompoHyDen: Hyperspectral Image Restoration via Nonconvex Componentwise Minimization

Комбінована Метрика Візуальної Якості Зображень Дистанційного Зондування На Основі Нейронної Мережі

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