A fast and HEVC-compatible perceptual video coding scheme using a transform-domain Multi-Channel JND model

Wang, Gang; Zhang, Yongfei; Li, Bo; Zhou, Mingliang

doi:10.1007/s11042-017-4914-4

Cited by 7 publications

(9 citation statements)

References 33 publications

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“…These visual masking effects are then combined with spatial CSF, luminance-based spatial masking and contrast masking to create a full JND profile. G. Wang et al in [22] propose a multi-channel DCT-based JND technique for HEVC; this method combines spatial CSF, spatial masking, contrast masking and temporal masking.…”

Section: Literature Reviewmentioning

confidence: 99%

“…where parameters g, h, j and k are set to values 3, 85, 90 and 3, respectively. These parameters are adopted in accordance with the chrominance masking-based psychovisual experiments conducted by G. Wang et al in [22]. Note that the functions in ( 5) and ( 6) can be utilized with chroma Cb and Cr data of any bit depth.…”

Section: Proposed Sc-paq Techniquementioning

confidence: 99%

“…In ( 5) and ( 6), variables μCb and μCr denote the mean raw sample values in a chroma Cb CB and a chroma Cr CB, respectively. Note that due to the significant similarity of Cb and Cr data in the YCbCr color space, the perceptual masking of chrominance Cb and Cr data can be achieved by virtue of the overlapping effect between chrominance saturation and luminance adaptation [22]. Therefore, high levels of (imperceptible) distortion can be applied to chroma data.…”

Section: Proposed Sc-paq Techniquementioning

confidence: 99%

“…It is important to note, however, that these techniques do not account for chrominance JND, which constitutes a significant shortcoming. This is primarily due to the fact that chroma data typically contains considerable HVS-based psychovisual redundancies [22]; therefore, this should be exploited in JND-based and visually lossless coding techniques.…”

Section: Introductionmentioning

confidence: 99%

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JND-Based Perceptual Video Coding for 4:4:4 Screen Content Data in HEVC

Prangnell

Sánchez

2018

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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The JCT-VC standardized Screen Content Coding (SCC) extension in the HEVC HM RExt + SCM reference codec offers an impressive coding efficiency performance when compared with HM RExt alone; however, it is not significantly perceptually optimized. For instance, it does not include advanced HVS-based perceptual coding methods, such as Just Noticeable Distortion (JND)-based spatiotemporal masking schemes. In this paper, we propose a novel JND-based perceptual video coding technique for HM RExt + SCM. The proposed method is designed to further improve the compression performance of HM RExt + SCM when applied to YCbCr 4:4:4 SC video data. In the proposed technique, luminance masking and chrominance masking are exploited to perceptually adjust the Quantization Step Size (QStep) at the Coding Block (CB) level. Compared with HM RExt 16.10 + SCM 8.0, the proposed method considerably reduces bitrates (Kbps), with a maximum reduction of 48.3%. In addition to this, the subjective evaluations reveal that SC-PAQ achieves visually lossless coding at very low bitrates. Table 1: The bitrate reductions (in bold green text) achieved by SC-PAQ compared with anchors: HM 16.10 + SCM 8.0 (left) and IDSQ [16] (right).

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Section: Literature Reviewmentioning

confidence: 99%

Section: Proposed Sc-paq Techniquementioning

confidence: 99%

Section: Proposed Sc-paq Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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JND-Based Perceptual Video Coding for 4:4:4 Screen Content Data in HEVC

Prangnell

Sánchez

2018

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…For the transform non-skip mode, the transform domain JND threshold is estimated by considering the contrast sensitivity function. In Reference [22], the JND threshold based on perceptual redundancy in both luma and chroma channels is incorporated in HEVC at transformation and quantization stages to achieve bitrate saving and complexity reduction.…”

Section: Introductionmentioning

confidence: 99%

High Efficiency Video Coding Compliant Perceptual Video Coding Using Entropy Based Visual Saliency Model

Zeeshan

Majid

2019

Entropy

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In past years, several visual saliency algorithms have been proposed to extract salient regions from multimedia content in view of practical applications. Entropy is one of the important measures to extract salient regions, as these regions have high randomness and attract more visual attention. In the context of perceptual video coding (PVC), computational visual saliency models that utilize the charactertistics of the human visual system to improve the compression ratio are of paramount importance. To date, only a few PVC schemes have been reported that use the visual saliency model. In this paper, we conduct the first attempt to utilize entropy based visual saliency models within the high efficiency video coding (HEVC) framework. The visual saliency map generated for each input video frame is optimally thresholded to generate a binary saliency mask. The proposed HEVC compliant PVC scheme adjusts the quantization parameter according to visual saliency relevance at the coding tree unit (CTU) level. Efficient CTU level rate control is achieved by allocating bits to salient and non-salient CTUs by adjusting the quantization parameter values according to their perceptual weighted map. The attention based on information maximization has shown the best performance on newly created ground truth dataset, which is then incorporated in a HEVC framework. An average bitrate reduction of 6 . 57 % is achieved by the proposed HEVC compliant PVC scheme with the same perceptual quality and a nominal increase in coding complexity of 3 . 34 % when compared with HEVC reference software. Moreover, the proposed PVC scheme performs better than other HEVC based PVC schemes when encoded at low data rates.

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