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Hyperspectral anomaly detection via memory‐augmented autoencoders

CAAI Transactions on Intelligence Technology 2023年第4期8卷 1274-1287页

作者： Zhe Zhao Bangyong Sun Faculty of Printing Packaging Engineering and Digital Media TechnologyXi'an University of TechnologyXi'anChina Norwegian Colour and Visual Computing Laboratory Norwegian University of Science and TechnologyGjovikNorway

Recently,the autoencoder(AE)based method plays a critical role in the hyperspectral anomaly detection ***,due to the strong generalised capacity of AE,the abnormal samples are usually reconstructed well along with the normal background ***,in order to separate anomalies from the background by calculating reconstruction errors,it can be greatly beneficial to reduce the AE capability for abnormal sample reconstruction while maintaining the background reconstruction performance.A memory‐augmented autoencoder for hyperspectral anomaly detection(MAENet)is proposed to address this challenging ***,the proposed MAENet mainly consists of an encoder,a memory module,and a ***,the encoder transforms the original hyperspectral data into the low‐dimensional latent ***,the latent representation is utilised to retrieve the most relevant matrix items in the memory matrix,and the retrieved matrix items will be used to replace the latent representation from the ***,the decoder is used to reconstruct the input hyperspectral data using the retrieved memory *** this strategy,the background can still be reconstructed well while the abnormal samples *** conducted on five real hyperspectral anomaly data sets demonstrate the superiority of the proposed method.

关键词： anomaly detection hyperspectral images memory autoencoder

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Dual Encoder-Decoder Shifted Window-Based Transformer Network for Polyp Segmentation with Self-Learning Approach

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3456-3469页

作者： Lijin, P. Ullah, Mohib Vats, Anuja Cheikh, Faouzi Alaya Kumar, Santhosh Nair, Madhu S. Cochin University of Science and Technology Artificial Intelligence & Computer Vision Laboratory Department of Computer Science Kerala Kochi682022 India Norwegian University of Science and Technology Gjovik2815 Norway Norwegian University of Science and Technology Norwegian Colour and Visual Computing Laboratory Gjovik2815 Norway

According to WHO reports, cancer is the leading cause of death worldwide. The second most prevalent cause of cancer-related death in both men and women is colorectal cancer (CRC). One potential approach for reducing the severity of colon cancer is to utilize automatic segmentation and detection of colorectal polyps in colonoscopy videos. This technology can assist endoscopists in quickly identifying colorectal disease, leading to earlier intervention and better patient Quality of Life (QoL). In this article, we propose a self-supervised transformer based dual encoder-decoder architecture named P-SwinNet for polyps segmentation in colonoscopy images. The P-SwinNet adapts the dual encoder-decoder type of model to enhance the feature maps by sharing multiscale information from the encoder to the decoder. The proposed model uses multiple dilated convolutions to enlarge the field of view to gather more information without increasing the computational cost and the loss of spatial information. We also leverage a large-scale unlabeled dataset for training our model using the self-learning strategy of Barlow twins. Additionally, to capture the long-range dependencies in the data, we used a shift window-based approach that computes global attention. We extensively evaluate our model against state-of-the-art algorithms. The quantitative results show that the proposed P-SwinNet achieves a mean dice score of 0.87 and a mean Intersection over Union (IoU) of 0.82 on five datasets used in our study. This performance demonstrates a substantial advancement over existing similar works, highlighting the advantage and novelty of our proposed approach in the field of medical image segmentation. © 2020 IEEE.

关键词： Convolution

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Radiometric spectral fusion of VNIR and SWIR hyperspectral cameras 29

Radiometric spectral fusion of VNIR and SWIR hyperspectral c...

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29th Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2021

作者： Grillini, Federico Thomas, Jean-Baptiste George, Sony The Norwegian Colour and Visual Computing Laboratory IDI-NTNU Gjøvik Norway

ISBN: (纸本)9780892083572

When two hyperspectral cameras are sensitive to complementary portions of the electromagnetic spectrum it is fundamental that the calibration processes conducted independently lead to comparable radiance values, especially if the cameras show a shared spectral interval. However, in practice, a perfect matching is hard to obtain, and radiance values that are expected to be similar might differ significantly. In the present study we propose to introduce an ulterior linear correcting factor in the radiometric calibration pipeline of two hyperspectral cameras, operating in the visible near infrared (VNIR) and short wave infrared (SWIR) intervals. The linearity properties of both cameras are preliminarily assessed, conducting acquisitions on five standardized targets, and highlighting noise at the sensors level and different illumination fields as the main causes of radiance mismatch. The correction step that we propose allows the retrieval of accurate and smoothly connected VNIR-SWIR reflectance factor curves. © 2021 Society for Imaging Science and Technology. All rights reserved.

关键词： Cameras

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Estimating visual difference between reproduction gamuts: Moving our pilot study from the lab to online delivery 29

Estimating visual difference between reproduction gamuts: Mo...

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29th Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2021

作者： High, Gregory Nussbaum, Peter Green, Phil The Norwegian Colour and Visual Computing Laboratory Norwegian University of Science and Technology Gjøvik Norway

ISBN: (纸本)9780892083572

Images reproduced for different output devices are known to be limited in the range of colours that can be reproduced. It is accepted that reproductions made with different print processes, and on different substrates, will not match, although the overall reproduction appearance can be optimized using an output rendering. However, the question remains: how different are they visually? This paper reports on a pilot study that tests whether visual difference can be reduced to a single dimensional scale using magnitude estimation. Subject to recent Covid restrictions, the experiment was moved from the lab to an online delivery. We compare the two methods of delivery: in-person under controlled viewing conditions, and online via a web-based interface where viewing conditions are unknown. © 2021 Society for Imaging Science and Technology.

关键词： Cell proliferation

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The impact of the Helmholtz-Kohlrausch effect on the appearance of near-white paper colours 29

The impact of the Helmholtz-Kohlrausch effect on the appeara...

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29th Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2021

作者： High, Gregory Green, Phil The Norwegian Colour and Visual Computing Laboratory Norwegian University of Science and Technology Gjøvik Norway

ISBN: (纸本)9780892083572

This paper investigates the impact of the Helmholtz-Kohlrausch effect on near-white substrate colours. As the luminance of the test colour (or its simulated reflectance in a soft-proof setup) approaches that of the adapting white point the viewing mode changes from ‘surface mode’ to ‘aperture mode’, and the appearance of the test colour becomes self-luminous. However, some substrates with optical brighteners fall close to this threshold between viewing modes, since the OBAs not only increase the perceived reflectance but also increase the H-K effect, where it is very prominent in bluish colours. For graphic arts content shown on a display system, this essentially breaks the soft-proofing paradigm. The practical application of this work relates to cross-media colour reproduction, where the lightness appearance of some substrates is not adequately described by their colorimetric values, and this may impact on choice of proofing strategies. © 2021 Society for Imaging Science and Technology.

关键词： Color

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colourlab image database: Geometric distortions 29

Colourlab image database: Geometric distortions

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29th Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2021

作者： Pedersen, Marius Amirshahi, Seyed Ali The Norwegian Colour and Visual Computing Laboratory Norwegian University of Science and Technology Gjøvik Norway

ISBN: (纸本)9780892083572

Over the years, a high number of different objective image quality metrics have been proposed. While some image quality metrics show a high correlation with subjective scores provided in different datasets, there still exists room for improvement. Different studies have pointed to evaluating the quality of images affected by geometrical distortions as a challenge for current image quality metrics. In this work, we introduce the colourlab Image Database: Geometric Distortions (CID:GD) with 49 different reference images made specifically to evaluate image quality metrics. CID:GD is one of the first datasets which include three different types of geometrical distortions;seam carving, lens distortion, and image rotation. 35 state-of-the-art image quality metrics are tested on this dataset, showing that apart from a handful of these objective metrics, most are not able to show a high performance. The dataset is available at www. colourlab. no/cid . © 2021 Society for Imaging Science and Technology.

关键词： Geometry

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Evaluation of text legibility in alternative imaging approaches to microfiche digitization

Evaluation of text legibility in alternative imaging approac...

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Archiving 2021

作者： Deborah, Hilda Mandai, Dipendra J. Norwegian Colour and Visual Computing Laboratory Department of Computer Science NTNU Norwegian University of Science and Technology Gjovik Norway

ISBN: (纸本)9780892083541

Microfiche was a common format used in microforms reproductions of documents, extensively used for archival storage before the move to digital formats. While contemporary documents are still available for digitization, others from older historical periods are no longer physically accessible for various reasons. In some cases, their microfiche copies are available, making microfiche digitization a must. However, a microfiche reader is not always available and, even then, it is a machine made for the purpose of reading and not for data collection. In this work, the performance two imaging devices are evaluated as alternatives to the traditional microfiche reader, by means of optical character recognition (OCR). Results show that this alternative surpasses the performance of a microfiche reader in terms of text legibility. © 2021 Society for Imaging Science and Technology.

关键词： Digital storage

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Quality is in the salient region of the image 18

Quality is in the salient region of the image

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18th Image Quality and System Performance Conference, IQSP 2021

作者： Seikavandi, Meisam Jamshidi Amirshahi, Seyed Ali Khaje Nasir University of Technology Tehran Iran The Norwegian Colour and Visual Computing Laboratory Norwegian University of Science and Technology Gjøvik Norway

The ultimate goal in any proposed Image Quality Metrics (IQMs) is to accurately predict the subjective quality scores given by observers. In the case of most IQMs the quality score is calculated by pooling the quality scores from what is referred to as a quality map of an image. While different pooling methods have been proposed, most such approaches use various types of a weighting average over the quality map to calculate the image quality score. One such approach is to use saliency maps as a weighting factor in our pooling process. Such an approach will result in giving a higher weight to the salient regions of the image. In this work we study if we can evaluate the quality of an image by only calculating the quality of the most salient region in the image. Such an approach could possibly reduce the computational time and power needed for image quality assessment. Results show that in most cases, depending on the saliency calculation method used, we can improve the accuracy of IQMs by simply calculating the quality of a region in the image which covers as low as 20% of the salient energy. © 2021, Society for Imaging Science and Technology

关键词： Image quality

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3D-Resnet Fused Attention for Autism Spectrum Disorder Classification 11th

3D-Resnet Fused Attention for Autism Spectrum Disorder Class...

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11th International Conference on Image and Graphics, ICIG 2021

作者： Chen, Xiangjun Wang, Zhaohui Cheikh, Faouzi Alaya Ullah, Mohib School of Computer Science and Cyberspace Security Hainan University Haikou China The Norwegian Colour and Visual Computing Laboratory Norwgian University of Science and Technology Trondheim Norway

ISBN: (纸本)9783030873578

Autism spectrum disorder (ASD) is a neuro development condition, early diagnosis of ASD traits is indispensable for applying effective treatment. Analysis of ASD based on deep learning (DL) has become an active research topic in the field of medical image analysis. However, the classification performance of the DL models is severely affected by the class imbalance of medical images. Recently, the combination of attention mechanism and Convolutional Neural Network (CNN) has significantly improved the performance of numerous classification and recognition tasks. Therefore, the attention mechanism has a promising prospect in improving the performance of CNN-based ASD diagnosis. This paper proposes a 3D-ResNet model with an attention subnet for ASD diagnosis. The model is constructed by the residual attention module, which is designed to mask redundant regions that are irrelevant to ASD diagnostic classification during the feature extraction process. The fMRI from Autism Imaging Data Exchange (ABIDE) was applied as the datasets and the experimental results show that the performance of the proposed approach is significantly better than that of conventional DL models. © 2021, Springer Nature Switzerland AG.

关键词： Diseases

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Examining spatial attributes for color deficient observers 26

Examining spatial attributes for color deficient observers

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26th Color Imaging: Displaying, Processing, Hardcopy, and Applications, Held at IS and T International Symposium on Electronic Imaging Science and Technology 2021

作者： Eschbach, R. Nussbaum, P. Norwegian Colour and Visual Computing Laboratory NTNU Norwegian University of Science and Technology Gjøvik Norway Monroe Community College RochesterNY United States

Color deficiency is a common affliction for males, with about 8% of the male population suffering from some form of - colloquial - color blindness. In common description, this is interpreted as the inability to perceive certain colors from a sensory standpoint. If that description is sufficiently complete, spatial attributes of the color signal should not influence the visual experience of a Color Deficient Observer (CDO). In this paper we describe the set-up and results of an experiment that is intended to vary the spatial attributes of a color deficiency test when shown to an observer. For this, we modified color vision charts to maintain their colorimetric attributes while varying spatial attributes and we measured color deficient observers with respect to their response accuracy and their response speed. We show results that indicate that there is a clear influence of color proximity in the responses. © 2021, Society for Imaging Science and Technology.

关键词： Color

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