SSIM-Based Game Theory Approach for Rate-Distortion Optimized Intra Frame CTU-Level Bit Allocation

Gao, Wei; Kwong, Sam; Zhou, Yu; Yuan, Hui

doi:10.1109/tmm.2016.2535254

Cited by 86 publications

(22 citation statements)

References 29 publications

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“…To quantitatively evaluate the relative performances of the three algorithms, we take Figure 8(a) as the standard timefrequency distribution image and measure algorithm performance by calculating the peak SNR (PSNR) [28,29] and the structural similarity (SSIM) [30,31] based on comparisons of the images generated under a noise background of varying SNR.…”

Section: Radar Signal Emitter Recognition Based On Eemd-gstmentioning

confidence: 99%

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Radar Signal Emitter Recognition Based on Combined Ensemble Empirical Mode Decomposition and the Generalized S‐Transform

Liu

Feng

Yin

et al. 2019

Mathematical Problems in Engineering

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Present radar signal emitter recognition approaches suffer from a dependency on prior information. Moreover, modern emitter recognition must meet the challenges associated with low probability of intercept technology and other obscuration methodologies based on complex signal modulation and must simultaneously provide a relatively strong ability for extracting weak signals under low SNR values. Therefore, the present article proposes an emitter recognition approach that combines ensemble empirical mode decomposition (EEMD) with the generalized S-transform (GST) for promoting enhanced recognition ability for radar signals with complex modulation under low signal-to-noise ratios in the absence of prior information. The results of Monte Carlo simulations conducted using various mixed signals with additive Gaussian white noise are reported. The results verify that EEMD suppresses the occurrence of mode mixing commonly observed using standard empirical mode decomposition. In addition, EEMD is shown to extract meaningful signal features even under low SNR values, which demonstrates its ability to suppress noise. Finally, EEMD-GST is demonstrated to provide an obviously better time-frequency focusing property than that of either the standard S-transform or the short-time Fourier transform.

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Section: Radar Signal Emitter Recognition Based On Eemd-gstmentioning

confidence: 99%

“…EEMD-ICA in[30] CEEMD in[31] EEMD-PCA in[32] Comparison of the structural similarity with other algorithms (SSIM).…”

mentioning

confidence: 99%

Radar Signal Emitter Recognition Based on Combined Ensemble Empirical Mode Decomposition and the Generalized S‐Transform

Liu

Feng

Yin

et al. 2019

Mathematical Problems in Engineering

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show abstract

“…On this basis, Structural Similarity (SSIM) is adopted to further screen the labeled areas with the relationship of "father and son", namely, SSIM shall be greater than 0.6. The structural similarity of the two labeled regions R x and R y is calculated in J-image, and the formula is as follows [19]: avoid the instability when the denominator is close to zero. In the case of the relationship of "father and son", the upper labeled region will replace the lower labeled region.…”

Section: Multi-bands Fusion Based On Information Entropymentioning

confidence: 99%

A Novel Segmentation Method for High Resolution Urban Remote Sensing Image Based on Improved JSEG Algorithm

Gu¹,

Li²

2017

IJSIP

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“…There are many perceptual quality prediction models, such as Structural Similarity Index Metric (SSIM), Gradient Magnitude Similarity Deviation (GMSD), picture wise Just Noticeable Difference (JND) [13], etc. With SSIM, the game theory was employed [14] to guide the CTU level bit allocation for intra frame. Moreover, SSIM based rate control algorithms were proposed in [15] and [16].…”

Section: Introductionmentioning

confidence: 99%

Perception-Based CTU Level Bit Allocation for Intra High Efficiency Video Coding

et al. 2019

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The conventional rate control algorithm does not fully consider the characteristics of the Human Visual System (HVS). To address this problem, in this paper, a perception based Coding Tree Unit (CTU) level bit allocation algorithm for intra High Efficiency Video Coding (HEVC) is proposed, which aims to minimize the perceptual distortion of each CTU under a given bit rate constraint. Firstly, to better represent perceptual distortion, Perceptually Weighted Mean Squared Error (PWMSE) is adopted instead of Mean Squared Error (MSE). Then, the relationship between Rate (R) and Perceptually Weighted Distortion (D p) is formulated by the proposed R-D p model. Finally, the perceptual weighting factor derived from the R-D p model is used to guide CTU level bit allocation. Experimental results show that the proposed algorithm achieves 6.27% bit rate reduction and 0.38 dB Bjøntegaard Delta Perceptually Weighted Peak Signal to Noise Ratio (BD-PWPSNR) gain on average. Under other seven quality evaluation metrics, the proposed algorithm achieves from 1.57% to 8.95% average bit rate reduction while maintaining the perceptual quality, which significantly outperforms the benchmark schemes. Moreover, the proposed perception-based CTU level bit allocation algorithm also maintains a high rate control accuracy, which reaches 99.997%. INDEX TERMS Perceptual coding, bit allocation, rate control, high efficiency video coding.

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SSIM-Based Game Theory Approach for Rate-Distortion Optimized Intra Frame CTU-Level Bit Allocation

Cited by 86 publications

References 29 publications

Radar Signal Emitter Recognition Based on Combined Ensemble Empirical Mode Decomposition and the Generalized S‐Transform

Radar Signal Emitter Recognition Based on Combined Ensemble Empirical Mode Decomposition and the Generalized S‐Transform

A Novel Segmentation Method for High Resolution Urban Remote Sensing Image Based on Improved JSEG Algorithm

Perception-Based CTU Level Bit Allocation for Intra High Efficiency Video Coding

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