- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Light Field Image Compression Using Generative Adversarial Network Based View Synthesis
摘要： Light ?eld (LF) has become an attractive representation of immersive multimedia content for simultaneously capturing both the spatial and angular information of the light rays. In this paper, we present a LF image compression framework driven by generative adversarial network (GAN) based sub-aperture image (SAI) generation and cascaded hierarchical coding structure. Speci?cally, we sparsely sample the SAIs in LF and propose the generative adversarial network of LF (LF-GAN) to generate the unsampled SAIs by analogy with adversarial learning conditioned on its surrounding contexts. In particular, LF-GAN learns to interpret both the angular and spatial context of the LF structure, and meanwhile generates intermediate hypothesis for the unsampled SAIs in a certain position. Subsequently, the sampled SAIs and the residues of the generated-unsampled SAIs are re-organized as pseudo-sequences and compressed by standard video codecs. Finally, the hierarchical coding structure is adopted for the sampled SAI to effectively remove the inter-view redundancies. During the training process of LF-GAN, the pixel-wise Euclidean loss as well as the adversarial loss are chosen as the optimization objective, such that sharp textures with less blurring in details can be produced. Extensive experimental results show that the proposed LF-GAN based LF image compression framework outperforms the state-of-the-art learning based LF image compression approach with on average 4.9% BD-rate reductions over multiple LF datasets.
关键词： adversarial learning,SAI synthesis,hierarchical coding,Light ?eld image compression
更新于2025-09-23 15:23:52
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Remote Sensing Image Compression in Visible/Near-Infrared Range Using Heterogeneous Compressive Sensing
摘要： Compressive sensing (CS) framework is very suitable for onboard image compression of high-resolution remote sensing cameras in the visible/near-infrared range (VI/NI-RSC) because it has the low-complexity in the sampling measurement stage. In this paper, we propose a new heterogeneous CS method for VI/NI-RSCs. Different from conventional CS methods evenly allocating sensing resources, the proposed method fully employs texture-feature information of remote sensing images to guide the allocation of sensing resources. More sensing resources are allocated to high-frequency regions, but fewer to low-frequency regions. The heterogeneous distribution of sensing resources obtains high reconstruction quality at the same compression performance, as well as high compression performance at the same level reconstructed quality. The shift of sensing resources is consistent with artificial image interpretations, i.e., human visual characteristics, where high-frequency regions, such as edges and textures, are the principal proof of the ground target identification. Experimental results indicate that the proposed method has better reconstruction quality than conventional CS method where texture-features are not utilized.
关键词： panchromatic images,remote sensing image compression,Heterogeneous compressive sensing (CS)
更新于2025-09-23 15:23:52
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Two-Dimensional Compressed Sensing Using Two-Dimensional Random Permutation for Image Encryption-then-Compression Applications
摘要： Block compressed sensing with random permutation (BCS-RP) has been shown to be very effective for image Encryption-then-Compression (ETC) applications. However, in the BCS-RP scheme, the statistical information of the blocks is disclosed, because the encryption is conducted within each small block of the image. To solve this problem, a two-dimension compressed sensing (2DCS) with 2D random permutation (2DRP) strategy for image ETC applications is proposed in this letter, where the 2DRP strategy is used for encrypting the image and the 2DCS scheme is used for compressing the encrypted image. Compared with the BCS-RP scheme, the proposed approach has two benefits. Firstly, it offers better security. Secondly, it obtains a significant gain of peak signal-to-noise ratio (PSNR) of the reconstructed-images.
关键词： image encryption,image compression,two-dimension compressed sensing,Encryption-then-Compression,two-dimension random permutation
更新于2025-09-23 15:22:29
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[ACM Press the 2018 International Conference - Porto, Portugal (2018.07.15-2018.07.17)] Proceedings of the 2018 International Conference on Mathematics and Statistics - ICoMS 2018 - Singular Value Decomposition and its Applications in Image Processing
摘要： The Singular Value Decomposition (SVD) is a highlight of linear algebra and has a wide range application in computer vision, statistics and machine learning. This paper reviews the main theorem of SVD and illustrates some applications of SVD in image processing. More specifically, we focus on image compression and matrix completion. The former is to convert the original full-rank pixel matrix to a well-approximated low-rank matrix and thus dramatically save the space, the latter is to recover a pixel matrix with a large number of missing entries by using nuclear norm minimization, in which some singular value thresholding algorithm will be used. For both applications, we conduct numerical experiments to show the performance and point out some possible improvements in the future.
关键词： Nuclear norm minimization,Matrix completion,Image compression,SVD
更新于2025-09-23 15:22:29
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Vector quantization using the improved differential evolution algorithm for image compression
摘要： Vector quantization (VQ) is a popular image compression technique with a simple decoding architecture and high compression ratio. Codebook designing is the most essential part in vector quantization. Linde–Buzo–Gray (LBG) is a traditional method of generation of VQ codebook which results in lower PSNR value. A codebook affects the quality of image compression, so the choice of an appropriate codebook is a must. Several optimization techniques have been proposed for global codebook generation to enhance the quality of image compression. In this paper, a novel algorithm called IDE-LBG is proposed which uses improved differential evolution algorithm coupled with LBG for generating optimum VQ codebooks. The proposed IDE works better than the traditional DE with modifications in the scaling factor and the boundary control mechanism. The IDE generates better solutions by efficient exploration and exploitation of the search space. Then the best optimal solution obtained by the IDE is provided as the initial codebook for the LBG. This approach produces an efficient codebook with less computational time and the consequences include excellent PSNR values and superior quality reconstructed images. It is observed that the proposed IDE-LBG find better VQ Codebooks as compared to IPSO-LBG, BA-LBG and FA-LBG.
关键词： Improved differential evolution (IDE) algorithm,Improved particle swarm optimization (IPSO) algorithm,Bat algorithm (BA),Firefly algorithm (FA),Vector quantization,Image compression,Codebook,Linde–Buzo–Gray (LBG) algorithm
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Compression of Hyperspectral Images Using Luminance Transform and 3D-DCT
摘要： DCT based transform techniques are popular in image compression. In this paper, luminance transform is applied to improve the compression performance of 3-D discrete cosine transform (3D-DCT) in hyperspectral images. The proposed scheme consists of two main steps. Firstly, luminance transform is performed on spectral band groups taking the first band image in a group as the reference. The aim of using luminance transform is to reduce the brightness and contrast difference within spectral band groups. Secondly, compression is performed by 3D-DCT followed by entropy encoding. The performance of the proposed approach is compared to 3D-DCT in terms of signal-to-noise ratio (SNR) and mean spectral angle (MSA). It is observed that applying luminance transform before 3D-DCT provides better results especially at low bit-rates.
关键词： hyperspectral image compression,luminance transform,3D-DCT
更新于2025-09-23 15:21:21
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Joint Image Compression and Encryption Using IWT with SPIHT, Kd-Tree and Chaotic Maps
摘要： Confidentiality and efficient bandwidth utilization require a combination of compression and encryption of digital images. In this paper, a new method for joint image compression and encryption based on set partitioning in hierarchical trees (SPIHT) with optimized Kd-tree and multiple chaotic maps was proposed. First, the lossless compression and encryption of the original images were performed based on integer wavelet transform (IWT) with SPIHT. Wavelet coefficients undergo diffusions and permutations before encoded through SPIHT. Second, maximum confusion, diffusion and compression of the SPIHT output were performed via the modified Kd-tree, wavelet tree and Huffman coding. Finally, the compressed output was further encrypted with varying parameter logistic maps and modified quadratic chaotic maps. The performance of the proposed technique was evaluated through compression ratio (CR) and peak-signal-to-noise ratio (PSNR), key space and histogram analyses. Moreover, this scheme passes several security tests, such as sensitivity, entropy and differential analysis tests. According to the theoretical analysis and experimental results, the proposed method is more secure and decreases the redundant information of the image more than the existing techniques for hybrid compression and encryption.
关键词： k-dimensional tree,chaotic maps,set partition in hierarchical trees,integer wavelet transform,encryption,image compression
更新于2025-09-23 15:21:01
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Handbook of Dynamic Data Driven Applications Systems || Light Field Image Compression
摘要： The light field image, also known as the plenoptic image, contains the information about not only the intensity of light in a scene but also the direction of the light rays in space. Since the light field image contains very rich photometric and geometric information, it will have very widespread application in the future. For example, immersive content capture for virtual and mixed reality presentation or depth from light field for auto driving applications. To be more specific, a light field image can be enhanced with physical models for an autonomous decision making process, which is also an important task of the Dynamic Data Driven Applications Systems (DDDAS). Besides, the rich geometry and photometric information contained in the light field can be updated with real-time measurements, which is a focus of DDDAS such as smart city related image and video processing tasks. However, to make the light field images easier to be utilized, one of the most important tasks is to compress the light field images efficiently so they can be easily distributed over the current communication infrastructure.
关键词： DDDAS,geometric,photometric,plenoptic image,compression,light field image
更新于2025-09-23 15:19:57
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Disparities selection controlled by the compensated image quality for a given bitrate
摘要： A stereoscopic image consists of two views rendering a depth sense. Indeed each eye is constrained to look at one view, and the small objects displacements across the two views are interpreted as an indication of depth. These displacements are exploited as speci?c inter-view redundancies from a compression viewpoint. The classical still compression scheme, called disparity-compensated compression scheme, compresses one view independently of the second view, and a block-based disparity map modeling the displacements is losslessly compressed. The difference between the original view and its disparity predicted view is then compressed and used by the decoder to compute the compensated view to improve the disparity predicted view. However, a proof of concept work has already shown that selecting disparities according to the compensated view, instead of the predicted view, yields increased rate-distortion performance. This paper derives from the JPEG-coder, a disparity-dependent analytic expression of the distortion induced by the compensated view. This expression is embedded into an algorithm with a reasonable numerical complexity approaching the performance obtained with the proof of concept work. The proposed algorithm, called fast disparity-compensated block matching algorithm, provides at the same bitrate an average performance increase as compared to the classical stereoscopic image coding schemes.
关键词： Stereoscopic image,Compression,Block matching algorithm,Disparity compensation,JPEG-distortion
更新于2025-09-23 15:19:57
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[ACM Press the 2nd International Conference - Las Vegas, NV, USA (2018.08.27-2018.08.29)] Proceedings of the 2nd International Conference on Vision, Image and Signal Processing - ICVISP 2018 - Perceptually Lossless Image Compression with Error Recovery
摘要： In many bandwidth constrained applications, lossless compression may be unnecessary, as only two to three times of compression can be achieved. An alternative way to save bandwidth is to adopt perceptually lossless compression, which can attain eight times or more compression without loss of important information. In this research, our first objective is to compare and select the best algorithm in the literature to achieve the compression ratio with perceptually lossless compression for still images. Our second objective is to demonstrate error concealment algorithms that can handle corrupted pixels due to transmission errors in communication channels. We have clearly achieved the above objectives using realistic images.
关键词： Image Compression,Error Concealment,Perceptually Lossless
更新于2025-09-19 17:15:36