Light-field compression using a pair of steps and depth estimation

An, Ping; Cao, Fengyin; Liu, Deyang; Wu, Qiang

doi:10.1364/oe.27.003557

Cited by 20 publications

(14 citation statements)

References 49 publications

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“…where H represents a linear operator [21,22]. Set the criterion H opt for selecting linear operator H on the basis of minimum error mean square value:…”

Section: Best Linear Estimationmentioning

confidence: 99%

Research on Low Frame Rate Video Compression Algorithm in the Context of New Media

Yang¹,

Xiang²,

2021

Security and Communication Networks

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When using the current method to compress the low frame rate video animation video, there is no frame rate compensation for the video image, which cannot eliminate the artifacts generated in the compression process, resulting in low definition, poor quality, and low compression efficiency of the compressed low frame rate video animation video. In the context of new media, the linear function model is introduced to study the frame rate video animation video compression algorithm. In this paper, an adaptive detachable convolutional network is used to estimate the offset of low frame rate video animation using local convolution. According to the estimation results, the video frames are compensated to eliminate the artifacts of low frame rate video animation. After the frame rate compensation, the low frame rate video animation video is divided into blocks, the CS value of the image block is measured, the linear estimation of the image block is carried out by using the linear function model, and the compression of the low frame rate video animation video is completed according to the best linear estimation result. The experimental results show that the low frame rate video and animation video compressed by the proposed algorithm have high definition, high compression quality under different compression ratios, and high compression efficiency under different compression ratios.

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“…where H represents a linear operator [21,22]. Set the criterion H opt for selecting linear operator H on the basis of minimum error mean square value:…”

Section: Best Linear Estimationmentioning

confidence: 99%

Research on Low Frame Rate Video Compression Algorithm in the Context of New Media

Yang¹,

Xiang²,

2021

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

“…Consequently, this might interfere with real-time capability. A further challenge is the required data bandwidth to transfer all the light field information, which in recent times does not appear to be a problem of the scale previously thought, due to the high compressibility of light field data [22]. Nevertheless, the most substantial issue concerns the physical representation of light fields.…”

Section: Light-field Displaysmentioning

confidence: 99%

AR Displays: Next-Generation Technologies to Solve the Vergence–Accommodation Conflict

et al. 2019

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Augmenting reality (AR) holds many benefits in how people perceive information and use it in their workflow or leisure activities. A cohesive AR experience has many components; nevertheless, the key is display technologies. The current industry standard for the core solution is still conventional stereoscopy, which has proven to be inadequate for near-work due to the caused vergence–accommodation conflict and the inability to precisely overlay the 3D content on the real world. To overcome this, next-generation technologies have been proposed. While the holographic method holds the highest potential of being the ultimate solution, its current level of maturity is not sufficient to yield a practical product. Consequently, the next solution for near-work-capable AR displays will be of another type. LightSpace Technologies have developed a static multifocal display architecture based on stacked liquid crystal-based optical diffuser elements and a synchronized high-refresh rate image projector. A stream of 2D image depth planes comprising a 3D scene is projected onto respective physically-separated diffuser elements, causing the viewer to perceive a scene as continuous and having all relevant physical as well as psychological depth cues. A system with six image depth planes yielding 6 cpd resolution and 72° horizontal field-of-view has been demonstrated to provide perceptually continuous accommodation over 3.2 Diopter range. A further optimization by using a conventional image combiner resulted in the compact and practical design of the AR display.

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“…Furthermore, the reconstruction algorithms play an excellent role in recovering the loss of spatial resolution or angular resolution in the LF image processing. The compression and reconstruction algorithms are mainly based on the multiple representations of LF images: hexagonal lenslet image, rectangular decoded image, SAIs, focus stack, and epipolar plane images (EPIs) (Huang et al, 2019a ; Wu et al, 2019 ). All of the above representations can reflect the angular and spatial characteristics of LF images.…”

Section: Introductionmentioning

confidence: 99%

Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack

Meng

Yang

et al. 2022

Front. Comput. Neurosci.

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Due to the complex angular-spatial structure, light field (LF) image processing faces more opportunities and challenges than ordinary image processing. The angular-spatial structure loss of LF images can be reflected from their various representations. The angular and spatial information penetrate each other, so it is necessary to extract appropriate features to analyze the angular-spatial structure loss of distorted LF images. In this paper, a LF image quality evaluation model, namely MPFS, is proposed based on the prediction of global angular-spatial distortion of macro-pixels and the evaluation of local angular-spatial quality of the focus stack. Specifically, the angular distortion of the LF image is first evaluated through the luminance and chrominance of macro-pixels. Then, we use the saliency of spatial texture structure to pool an array of predicted values of angular distortion to obtain the predicted value of global distortion. Secondly, the local angular-spatial quality of the LF image is analyzed through the principal components of the focus stack. The focalizing structure damage caused by the angular-spatial distortion is calculated using the features of corner and texture structures. Finally, the global and local angular-spatial quality evaluation models are combined to realize the evaluation of the overall quality of the LF image. Extensive comparative experiments show that the proposed method has high efficiency and precision.

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Light-field compression using a pair of steps and depth estimation

Cited by 20 publications

References 49 publications

Research on Low Frame Rate Video Compression Algorithm in the Context of New Media

Research on Low Frame Rate Video Compression Algorithm in the Context of New Media

AR Displays: Next-Generation Technologies to Solve the Vergence–Accommodation Conflict

Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack

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