Perceptual Video Coding Based on Visual Saliency Modulated Just Noticeable Distortion

2019 ◽  
Author(s):  
Jing Cui ◽  
Ruiqin Xiong ◽  
Xinfeng Zhang ◽  
Shanshe Wang ◽  
Siwei Ma
Keyword(s):  
Video Coding ◽  
Visual Saliency ◽  
Just Noticeable Distortion ◽  
Perceptual Video Coding

Stereoscopic Perceptual Video Coding Based on Just-Noticeable-Distortion Profile

2011 ◽  
Vol 57 (2) ◽  
pp. 572-581 ◽  
Author(s):  
Lei Zhang ◽  
Qiang Peng ◽  
Qiong-Hua Wang ◽  
Xiao Wu
Keyword(s):  
Video Coding ◽  
Just Noticeable Distortion ◽  
Perceptual Video Coding

Visual saliency based perceptual video coding in HEVC

2016 ◽  
Author(s):  
Henglu Wei ◽  
Xin Zhou ◽  
Wei Zhou ◽  
Chang Yan ◽  
Zhemin Duan ◽  
...  
Keyword(s):  
Video Coding ◽  
Visual Saliency ◽  
Perceptual Video Coding

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

Entropy ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. 964 ◽  
Author(s):  
Muhammad Zeeshan ◽  
Muhammad Majid
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Visual Saliency ◽  
Quantization Parameter ◽  
High Efficiency Video Coding ◽  
Saliency Model ◽  
Salient Regions ◽  
Perceptual Video Coding ◽  
Visual Saliency Model ◽  
Visual Saliency Models

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.

scholarly journals Perceptual Video Coding Scheme Using Just Noticeable Distortion Model Based on Entropy Filter

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1095 ◽  
Author(s):  
Cui ◽  
Peng ◽  
Jiang ◽  
Chen ◽  
Yu
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Rate Distortion ◽  
Control Factor ◽  
Quality Loss ◽  
High Definition ◽  
Distortion Compensation ◽  
Just Noticeable Distortion ◽  
Perceptual Video Coding

Because perceptual video coding (PVC) can reduce bitrates with negligible visual quality loss in video compression, a PVC scheme based on just noticeable distortion (JND) model is proposed for ultra-high definition video. Firstly, the proposed JND model is designed, considering the spatial JND characteristics such as contrast sensitivity, luminance adaptation and saliency weight factor. Secondly, in order to perform precise JND suppression, the Gauss differential entropy (GDE) filter is designed to divide the image into smooth and complex texture region. Thirdly, through incorporating the proposed JND model into the encoding process, the transform coefficients are suppressed in harmonization with the transform/quantization process of high efficiency video coding (HEVC). In order to achieve the JND suppression effectively, a distortion compensation factor and distortion compensation control factor are incorporated to control the extent of distortion in the rate distortion optimization process. The experimental results show that the proposed PVC scheme can achieve a remarkable bitrate reduction of 32.98% for low delay (LD) configuration and 28.61% for random access (RA) configuration with a negligible subjective quality loss. Meanwhile, the proposed method only causes about average 12.94% and 22.45% encoding time increase under LD and RA configuration compared with an HEVC reference software, respectively.

A Fast Perceptual Surveillance Video Coding (PSVC) Based on Background Model-Driven JND Estimation

2020 ◽  
pp. 2155006
Author(s):  
Gang Wang ◽  
Mingliang Zhou ◽  
Haiheng Cao ◽  
Bin Fang ◽  
Shiting Wen ◽  
...  
Keyword(s):  
Video Coding ◽  
Estimation Method ◽  
Background Modeling ◽  
Video Codec ◽  
Background Model ◽  
Surveillance Video ◽  
Time Saving ◽  
Model Driven ◽  
Just Noticeable Distortion ◽  
Perceptual Video Coding

Perceptual video coding (PVC) optimization has been an important video coding technique, which can be consistent with the perception characteristics of the human visual system (HVS). Currently, PVC schemes incorporating the just noticeable distortion (JND) model can obtain better performance gain in all PVC schemes. To further accelerate the JND computation for real-time video coding applications (e.g. surveillance video coding and conference video coding), this paper proposes a fast perceptual surveillance video coding (PSVC) scheme based on background model-driven JND estimation method. First, to utilize the surveillance scene characteristics, the computation complexity of JND estimation can be significantly decreased by reusing the content complexity of background regions. Then we apply the perceptive video coding scheme into the background modeling-based surveillance video codec. The proposed scheme adopts background modeling frame as background anchor. Experimental results show that the proposed scheme can yield remarkable time saving of 42.33% maximum and on average 34.76% with approximate bitrate reductions and similar subjective quality, compared to HEVC and other state-of-the-art schemes.

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