In this paper, we present a new motion estimation architecture for large displacements estimation. An efficient differential block recursive algorithm is used to orient searching for a match and save computation power...
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ISBN:
(纸本)081941638X;9780819416384
In this paper, we present a new motion estimation architecture for large displacements estimation. An efficient differential block recursive algorithm is used to orient searching for a match and save computation power. Multiresolution and multiprediction approaches accelerate the algorithm convergence. Data multiplexing and pipeline allow real-time processing for standard video frequencies such as CCIR 601.
This paper presents the principle to enhance the spatial 2D resolution of spatial 2D resolution and the possibility of available limitation of maximum resolution. The paper also reports on image signal processing for ...
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ISBN:
(纸本)081941638X;9780819416384
This paper presents the principle to enhance the spatial 2D resolution of spatial 2D resolution and the possibility of available limitation of maximum resolution. The paper also reports on image signal processing for 2D high definition pictures and the hanging-up piezoelectric bimorph construction designed to improve both horizontal and vertical resolution respectively by one time. The regenerated signal can be compatible with current TV mode.
This paper presents a deep learning-based audio-in-image watermarking scheme. Audio-in-image watermarking is the process of covertly embedding and extracting audio watermarks on a cover-image. Using audio watermarks c...
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ISBN:
(纸本)9781728185514
This paper presents a deep learning-based audio-in-image watermarking scheme. Audio-in-image watermarking is the process of covertly embedding and extracting audio watermarks on a cover-image. Using audio watermarks can open up possibilities for different downstream applications. For the purpose of implementing an audio-in-image watermarking that adapts to the demands of increasingly diverse situations, a neural network architecture is designed to automatically learn the watermarking process in an unsupervised manner. In addition, a similarity network is developed to recognize the audio watermarks under distortions, therefore providing robustness to the proposed method. Experimental results have shown high fidelity and robustness of the proposed blind audio-in-image watermarking scheme.
Learning-based compression systems have shown great potential for multi-task inference from their latent-space representation of the input image. In such systems, the decoder is supposed to be able to perform various ...
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ISBN:
(纸本)9781728185514
Learning-based compression systems have shown great potential for multi-task inference from their latent-space representation of the input image. In such systems, the decoder is supposed to be able to perform various analyses of the input image, such as object detection or segmentation, besides decoding the image. At the same time, privacy concerns around visual analytics have grown in response to the increasing capabilities of such systems to reveal private information. In this paper, we propose a method to make latent-space inference more privacy-friendly using mutual information-based criteria. In particular, we show how organizing and compressing the latent representation of the image according to task-specific mutual information can make the model maintain high analytics accuracy while becoming less able to reconstruct the input image and thereby reveal private information.
Quanta image sensors are a novel paradigm in image sensor technology. Their direct application to quanta image sensors-based imaging systems is challenging because a bit-plane image is a set of binary images. In this ...
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ISBN:
(纸本)9798331529543;9798331529550
Quanta image sensors are a novel paradigm in image sensor technology. Their direct application to quanta image sensors-based imaging systems is challenging because a bit-plane image is a set of binary images. In this paper, we introduce spatiotemporal priors based on the intensity invariance and smoothness characteristics of the motion vector. Specifically, we model when the image sequences align with the correct motion vector, the spatiotemporal structure becomes more consistent. Moreover, the spatial smoothness prior is incorporated through the smoothing filtering of the evaluation metrics of motion vector candidates. The experimental results show that the proposed method is more effective than conventional methods.
This paper presents a concise end-to-end visual analysis motivated super-resolution model VASR for image reconstruction. Compatible with the existing machine vision feature coding framework, the features extracted fro...
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ISBN:
(纸本)9781665475921
This paper presents a concise end-to-end visual analysis motivated super-resolution model VASR for image reconstruction. Compatible with the existing machine vision feature coding framework, the features extracted from the machine vision task model are super-resolution amplified to reconstruct the original image for human vision. The experimental results show that without additional bit-streams, VASR can well complete the task of image reconstruction based on the extracted machine features, and has achieved good results on COCO, Openimages, TVD, and DIV2K datasets.
The guiding principle of this study is to find an optimum way to simplify the contours produced by a second generation coding scheme based on morphological segmentation. For this purpose, evaluations of existing metho...
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ISBN:
(纸本)081941638X;9780819416384
The guiding principle of this study is to find an optimum way to simplify the contours produced by a second generation coding scheme based on morphological segmentation. For this purpose, evaluations of existing methods for contour simplification are carried out first. Based on the human visual phenomenon, a new nonlinear filter by means of majority operation is designed to simplify the contours in order to obtain an optimum compromise between the cost for contour coding and visual quality. Applications for region-based still image coding and video coding are demonstrated. Experimental results have shown an average of 20% reduction of bits for contour coding while keeping good visual quality.
Baseband image communication systems using code division multiple access are proposed. We investigate such a system using fixed-length pseudonoise (PN) codes and one using variable-length PN codes. We can find that th...
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ISBN:
(纸本)081941638X;9780819416384
Baseband image communication systems using code division multiple access are proposed. We investigate such a system using fixed-length pseudonoise (PN) codes and one using variable-length PN codes. We can find that the number of channels can be reduced when the latter is employed. Such a situation leads us to employ chaotic sequences, whose code-lengths can be arbitrarily chosen, for such variable-length PN codes.
This paper proposes Graph Grouping (GG) loss for metric learning and its application to face verification. GG loss predisposes image embeddings of the same identity to be close to each other, and those of different id...
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ISBN:
(纸本)9781728180687
This paper proposes Graph Grouping (GG) loss for metric learning and its application to face verification. GG loss predisposes image embeddings of the same identity to be close to each other, and those of different identities to be far from each other by constructing and optimizing graphs representing the relation between images. Further, to reduce the computational cost, we propose an efficient way to compute GG loss for cases where embeddings are L-2 normalized. In experiments, we demonstrate the effectiveness o(f) the proposed method for face verification on the VoxCeleb dataset. The results show that the proposed GG loss outperforms conventional losses for metric learning.
The digital fish provenance and quality tracking system is essential for the seafood supply chain. As a part of this system, we develop a vision-based fish processing system to automatically perform fish freshness est...
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ISBN:
(纸本)9781728180687
The digital fish provenance and quality tracking system is essential for the seafood supply chain. As a part of this system, we develop a vision-based fish processing system to automatically perform fish freshness estimation, size measurement and species classification. Under the constrained illumination environment, our system is able to auto-process the fish selection, thus greatly reduce the human labour and bring trust and efficiency to the seafood supply chain from catch to market.
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