Recent Advances in Computational Photography

Dai, Qionghai; Wu, Jiamin; Fan, Jian; Xu, Feng; Cao, Xun

doi:10.1049/cje.2018.10.006

Cited by 5 publications

(2 citation statements)

References 33 publications

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“…2.1 Problem Formulation Fig. 1 shows an end-to-end chain of visual communication system, which consists of five major parts, the light and scene P, imaging system and representation (denoted as function 𝐹 𝑅 ) [17], processing and communication (𝐹 𝐸 ), display system and viewing condition (𝐹 𝐷 ) and the HVS (𝐹 𝐻𝑉 𝑆 ).…”

Section: Problem Formulation and Framework Of Perceptual Video Codingmentioning

confidence: 99%

A Survey on Perceptually Optimized Video Coding

Zhang¹,

Zhu²,

Jiang³

et al. 2021

Preprint

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Videos are developing in the trends of Ultra High Definition (UHD), High Frame Rate (HFR), High Dynamic Range (HDR), Wide Color Gammut (WCG) and high fidelity, which provide users with more realistic visual experiences. However, the amount of video data increases exponentially and requires high efficiency video compression for storage and network transmission. Perceptually optimized video coding aims to exploit visual redundancies in videos so as to maximize compression efficiency. In this paper, we present a systematic survey on the recent advances and challenges on perceptually optimized video coding. Firstly, we present problem formulation and framework of perceptually optimized video coding, which includes visual perception modelling, visual quality assessment and perception guided coding optimization. Secondly, the recent advances on visual factors, key computational visual models and quality assessment models are presented. Thirdly, we do systematic review on perceptual video coding optimizations from four key aspects, which includes perceptually optimized bit allocation, rate-distortion optimization, transform and quantization, filtering and enhancement. In each part, problem formulation, working flow, recent advances, advantages and challenges are presented. Fourthly, perceptual coding performance of latest coding standards and tools are experimentally analyzed. Finally, challenging issues and future opportunities on perceptual video coding are identified.CCS Concepts: • Computing methodologies → Image compression.

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Section: Problem Formulation and Framework Of Perceptual Video Codingmentioning

confidence: 99%

A Survey on Perceptually Optimized Video Coding

Zhang¹,

Zhu²,

Jiang³

et al. 2021

Preprint

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“…Phase retrieval (PR), i.e. the recovery of the original image from non-linear measurements, arises in many optical imaging applications [1][2][3][4]. Since the non-linear nature of the sampling operator, the imaging inverse problems are non-linear and non-convex.…”

Section: Introductionmentioning

confidence: 99%

Supervised dual tight frame learning with deep thresholding network for phase retrieval

Shi

Lian

2022

IET Image Processing

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Data-driven tight frames are popular for solving imaging inverse problems. However, the imaging quality is limited by the representation ability of single tight frame and thresholds tuned manually. In this work, a supervised dual tight frame learning framework fused with an elaborated deep thresholding network (DTN) is proposed, and the issue of low-quality reconstructions in previous phase retrieval (PR) algorithms is addressed. To effectively learn dual tight frames, a loss function is formed using the mean square error, tight constraint, dual constraint, and sparse constraint terms. Moreover, to determine the thresholds adaptively, the thresholds are extracted from the frame coefficients via DTN. By an end-to-end supervised learning manner, the dual tight frames and DTN are jointly trained from labels and their counterparts corrupted by Gaussian noise. Using the Gaussian denoiser constructed by dual tight frames, a regularisation model is firstly designed, and then exploited to formulate a PR optimisation problem. The image filtering and image updating steps are performed alternatively for solving this problem. Particularly, the image updating subproblem is tackled by an inertial epigraph solver. The simulation experiments show that the proposed PR algorithm can obtain higher-quality reconstructions compared with the benchmark ones.

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