Pixel-Domain Just Noticeable Difference Modeling with Heterogeneous Color Features
(This article belongs to the Section Intelligent Sensors)
Abstract
:1. Introduction
- (1)
- We carefully extract the color features that affect perception in the image, and on this basis, analyze the interaction relationship between color regions from the perspective of visual energy competition; then, accordingly propose color contrast intensity.
- (2)
- According to the characteristics of visual perception, color complexity and color distribution dispersion are regarded as visual suppression sources, and color contrast intensity is regarded as a visual stimulus source. Then, they are unified to information communication framework to quantify the degree of influence on perception.
- (3)
- The color uncertainty and the color saliency are applied to improve the conventional JND model, taking the masking and attention effect into consideration, wherein color saliency serves as an adjusting factor to modulate the masking effect based on color uncertainty.
2. Analysis of Color Feature Parameters
2.1. Existing Color Feature Parameters
2.2. Feasibility Analysis of Heterogeneous Color Feature Fusion
2.3. Interaction Analysis between Color Feature Quantities
- (1)
- With the same dispersion, the larger the homogeneous color area is, the more visual energy allocated to this color area compared with other color areas.
- (2)
- On the condition of same area proportion, if the distribution of one homogeneous color region is more concentrated than that of other regions, it will pose a positive stimulation effect on vision and vice versa.
- (3)
- As the distance between different color regions and the fixation point increases, the competitive relationship gradually weakens.
3. The Proposed JND Model
3.1. Color Uncertainty Measurement
3.2. Color Saliency Measurement
3.3. The Proposed JND Model
4. Experimental Results and Analysis
4.1. Noise Injection Method
4.2. Ablation Experiments
4.3. Comparison Experiments
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Color Feature Parameter | Symbol | Effect |
---|---|---|
Color Complexity | Masking | |
Color Edge Intensity | Saliency | |
Color Distribution Position | Saliency | |
Color Perception Difference | Saliency | |
Color Distribution Dispersion | Masking | |
Color Area Proportion | Saliency |
Subjective Score | Scoring Criteria |
---|---|
0 | The right figure has the same subjective quality as the left figure. |
−1 | The right image is slightly worse than the left image. |
−2 | The right image is of poorer subjective quality than the left image. |
−3 | The right image is much worse than the left image. |
Image Name | Wu2017 [15] | Zeng2019 [59] | Liu2020 [60] | Li2022 [61] | Proposed | |||||
---|---|---|---|---|---|---|---|---|---|---|
PSNR (dB) | MOS | PSNR | MOS | PSNR | MOS | PSNR | MOS | PSNR | MOS | |
T1 | 36.51 | −0.32 | 35.85 | −0.30 | 36.29 | −0.30 | 31.00 | −0.20 | 32.03 | −0.06 |
T2 | 35.47 | −0.30 | 35.27 | −0.30 | 36.34 | −0.26 | 31.72 | −0.16 | 32.23 | −0.06 |
T3 | 36.39 | −0.24 | 35.78 | −0.22 | 36.32 | −0.24 | 32.04 | −0.18 | 28.94 | −0.10 |
T4 | 31.51 | −0.22 | 34.74 | −0.12 | 33.55 | −0.08 | 32.25 | −0.08 | 31.58 | −0.06 |
T5 | 35.21 | −0.24 | 36.25 | −0.26 | 36.75 | −0.18 | 34.67 | −0.10 | 31.92 | −0.10 |
T6 | 33.99 | −0.32 | 36.43 | −0.28 | 35.35 | −0.22 | 34.92 | −0.10 | 34.34 | −0.08 |
T7 | 33.80 | −0.34 | 33.41 | −0.40 | 33.80 | −0.36 | 29.35 | −0.34 | 28.25 | −0.14 |
T8 | 34.69 | −0.28 | 36.84 | −0.24 | 37.32 | −0.18 | 34.80 | −0.12 | 34.06 | −0.06 |
T9 | 34.06 | −0.16 | 36.38 | −0.22 | 35.14 | −0.18 | 33.36 | −0.10 | 29.81 | −0.08 |
T10 | 36.95 | −0.24 | 36.52 | −0.30 | 37.21 | −0.26 | 32.52 | −0.16 | 35.01 | −0.06 |
Avg | 34.86 | −0.27 | 35.75 | −0.26 | 35.81 | −0.23 | 32.66 | −0.15 | 31.82 | −0.08 |
I1 | 35.90 | −0.28 | 36.16 | −0.22 | 37.97 | −0.16 | 37.09 | −0.14 | 30.81 | −0.12 |
I2 | 31.40 | −0.40 | 35.62 | −0.30 | 35.44 | −0.30 | 32.46 | −0.20 | 31.71 | −0.08 |
I3 | 34.57 | −0.22 | 36.52 | −0.22 | 37.07 | −0.18 | 35.66 | −0.12 | 30.48 | −0.10 |
I4 | 33.92 | −0.34 | 34.21 | −0.24 | 34.70 | −0.20 | 29.58 | −0.12 | 27.55 | −0.08 |
I5 | 34.76 | −0.22 | 34.52 | −0.20 | 35.52 | −0.16 | 29.81 | −0.12 | 27.76 | −0.06 |
I6 | 33.17 | −0.26 | 36.39 | −0.22 | 36.44 | −0.12 | 34.77 | −0.10 | 31.13 | −0.10 |
I7 | 34.87 | −0.40 | 35.67 | −0.30 | 37.21 | −0.22 | 33.57 | −0.10 | 30.94 | −0.06 |
I8 | 35.90 | −0.34 | 36.01 | −0.30 | 37.53 | −0.18 | 33.72 | −0.08 | 33.24 | −0.12 |
I9 | 28.62 | −0.14 | 36.49 | −0.06 | 33.26 | −0.06 | 33.21 | −0.06 | 29.60 | −0.06 |
I10 | 36.16 | −0.24 | 35.21 | −0.14 | 35.69 | −0.10 | 30.69 | −0.08 | 30.66 | −0.08 |
Avg | 33.93 | −0.28 | 35.68 | −0.22 | 36.08 | −0.17 | 33.06 | −0.11 | 30.39 | −0.09 |
L1 | 38.34 | −0.20 | 38.30 | −0.14 | 38.04 | −0.12 | 37.58 | −0.04 | 32.00 | −0.06 |
L2 | 36.72 | −0.18 | 33.33 | −0.18 | 33.58 | −0.14 | 29.13 | −0.08 | 27.87 | −0.08 |
L3 | 34.09 | −0.18 | 36.93 | −0.16 | 37.89 | −0.14 | 35.14 | −0.08 | 30.96 | −0.06 |
L4 | 34.83 | −0.24 | 35.62 | −0.18 | 35.84 | −0.12 | 33.07 | −0.10 | 34.01 | −0.14 |
L5 | 37.52 | −0.24 | 35.35 | −0.24 | 35.41 | −0.22 | 30.80 | −0.12 | 30.17 | −0.10 |
L6 | 34.71 | −0.16 | 31.87 | −0.14 | 31.56 | −0.10 | 25.96 | −0.08 | 24.49 | −0.06 |
L7 | 40.20 | −0.16 | 37.66 | −0.14 | 38.30 | −0.08 | 35.43 | −0.08 | 35.82 | −0.08 |
L8 | 36.47 | −0.28 | 36.70 | −0.30 | 37.08 | −0.24 | 34.30 | −0.10 | 33.83 | −0.08 |
L9 | 37.62 | −0.26 | 35.02 | −0.26 | 35.51 | −0.22 | 31.69 | −0.16 | 31.31 | −0.10 |
L10 | 37.45 | −0.18 | 33.02 | −0.32 | 33.22 | −0.28 | 28.10 | −0.20 | 28.21 | −0.12 |
Avg | 36.80 | −0.21 | 35.38 | −0.21 | 35.64 | −0.17 | 32.12 | −0.10 | 30.87 | −0.09 |
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Hu, T.; Yin, H.; Wang, H.; Sheng, N.; Xing, Y. Pixel-Domain Just Noticeable Difference Modeling with Heterogeneous Color Features. Sensors 2023, 23, 1788. https://doi.org/10.3390/s23041788
Hu T, Yin H, Wang H, Sheng N, Xing Y. Pixel-Domain Just Noticeable Difference Modeling with Heterogeneous Color Features. Sensors. 2023; 23(4):1788. https://doi.org/10.3390/s23041788
Chicago/Turabian StyleHu, Tingyu, Haibing Yin, Hongkui Wang, Ning Sheng, and Yafen Xing. 2023. "Pixel-Domain Just Noticeable Difference Modeling with Heterogeneous Color Features" Sensors 23, no. 4: 1788. https://doi.org/10.3390/s23041788