Dr. Jing Xing Profile

Dr. Jing Xing

Research Scientist at FAA

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Publications (3)

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Proceedings Article | 8 August 2003 Paper

An image compression model based on the human visual system

Jing Xing

Proceedings Volume 5108, (2003) https://doi.org/10.1117/12.485820

KEYWORDS: Visualization, Image processing, Visual process modeling, Image compression, Image filtering, Visual system, Visual cortex, Cognitive modeling, Image visualization, Contrast sensitivity

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Most algorithms of image processing treat an image homogeneously, while the human visual system processes a retinal image differently in the foveal and peripheral visual fields. It has been known that contrast sensitivity, spatial resolution and color discrimination of the visual system decrease from the fovea to the periphery. Moreover, recent psychophysical results showed that the spatial interactions between neighboring parts of a visual image are fundamentally different in the fovea and periphery. The perception of a visual stimulus can be suppressed or enhanced by the presence of other stimuli in its surround region. The spatial suppression in the periphery was much stronger than that in the fovea. In this report, we built an image processing model based on the neurophysiology of the human visual cortex to explore the possible impacts of the spatial interactions on image perception. We first adjusted model parameters to make the model have the same performance as human subjects had in perceiving foveal and peripheral images respectively. With those parameters, we simulated the image processing by the fovea and peripheral vision. We found that the strong spatial suppression in the periphery resulted in image boundary segmentation and salient target extraction. The response to a uniform image region was suppressed while the response to the boundary or salient regions remained. With this strategy, the visual information processed by the human cognition system is largely reduced. Based on these findings, we proposed a foveal-peripheral model for image compression and other possible applications.

Proceedings Article | 17 June 2003 Paper

Contrast-discrimination and contrast-appearance require different visual mechanisms

Jing Xing

Proceedings Volume 5007, (2003) https://doi.org/10.1117/12.473940

KEYWORDS: Image quality, Image processing, Visualization, Visual process modeling, Visual system, Quality measurement, Solids, Visual cortex, Neurons, Data modeling

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Image fidelity refers to the ability of discriminating the differences between two images, while image quality refers to the preference of one image over another image. Many image fidelity predictors adapted the results from contrast discrimination experiments. It is questionable whether these models can be used for image quality assessment. Image quality judgment mostly occurs to suprathreshold images and the judgment generally cares about the image appearance rather than the subtle differences between two images. In this report, we presented psychophysical evidence that image perception and discrimination have different mechanism in terms of spatial interactions. We built an image processing model of the primary visual system to simulate contrast perception and contrast discrimination at the suprathreshold level. By introducing different neuronal integration mechanisms (i.e., decision rules) to the same model structure, the model was able to predict the perceived contrast and contrast discrimination thresholds of a target embedded in a complex image. Our simulations showed that the contextual effect was significant in contrast perception and thus should not be ignored by the models of image quality measurement. With further calibrations, the 2-D output of the model can be used to as an image quality metric to predict perceptual differences in images.

Proceedings Article | 30 May 2002 Paper

Functional roles of center-surround interactions in visual image processing

Jing Xing

Proceedings Volume 4662, (2002) https://doi.org/10.1117/12.469506

KEYWORDS: Image processing, Visualization, Visual process modeling, Image visualization, Image segmentation, Performance modeling, Video, Image compression, Visual cortex, Data modeling

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The perception of a visual stimulus is affected by the presence of other stimuli in its surround region. The perceived central contrast can be suppressed or enhanced by the surrounds. Our previous psychophysical results showed that both surround suppression and enhancement existed in the foveal vision while only suppression existed in the peripheral vision. Moreover, the suppression in the periphery was much stronger than that in the fovea. In this report, we built an image processing model for the vision system with lateral connections embedded. We first adjusted model parameters to make the model have the same performance as human subjects had in contrast perception experiments in fovea and periphery respectively. With those parameters, we then analyzed the functions of lateral connections in image perception. We found that: 1) With foveal parameters, lateral interactions served the purpose of gain control and image regularization. The contrast response in the fovea was modulated by the global image through lateral connections. 2) With peripheral parameters, lateral interactions resulted in image boundary segmentation. The response to a uniform image region was suppressed while the response to the boundary regions remained. The results suggest that a visual image be encoded differently by foveal and peripheral vision. The possible impacts of this feature on image compression were discussed.

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