Abstract
In order to provide high transmission efficiency and visual quality for the color image/video in internet, effective estimation of its inherent just noticeable distortion (JND) is continuously an important topic. In this paper, a discrete cosine transform (DCT)-based perceptual model for estimating spatio-temporal JNDs of color videos is presented. Firstly, the compound masking adjustment integrated with different spatial masking factors is proposed. Based on the base detection threshold for DCT coefficients in luminance and chrominance components of the color image, the adjustment combined by luminance masking, pattern-based contrast masking, and cross masking is exploited to measure visibility thresholds for luminance component, while the adjustment induced by the variance-based statistical properties is utilized to measure visibility thresholds for chrominance components. Then, the local temporal statistics of luminance component are considered to design the structure-based temporal masking adjustment for further estimating visibility thresholds of video signals. To verify the proposed method, a subjective viewing test is designed and a fair rating process of evaluating the visual quality is carried out under the specified viewing condition. Experimental results show that the proposed method is able to measure more visual distortion tolerance than the existing color-based methods at high visual quality.
Highlights
Since human eyes are the receiver of the visual information, utilizing the properties of human visual system (HVS) is helpful for increasing the performance of the image and video processing algorithms
The just noticeable distortion (JND) models developed for images combined with temporal properties of the HVS are exploited in the video codec to improve its coding efficiency while the visual quality is acceptable under low bit rates [9]–[14]
We propose the luminance-dominated structure-based temporal masking adjustment to extend the above spatial JND to the spatio-temporal JND of color video signals by considering co-existence of inter-frame difference and the uncertainty information of inter-frame variation
Summary
Since human eyes are the receiver of the visual information, utilizing the properties of human visual system (HVS) is helpful for increasing the performance of the image and video processing algorithms. A DCT-based JND method integrated with the proposed compound spatial masking adjustment and structure-based temporal masking adjustment for color video signals is presented.
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