Display device backlight optimization method and server based on deep learning

Abstract

This invention discloses a deep learning-based method and server for optimizing backlight in display devices. The method constructs manifold evolution trajectory features from the display content frame sequence to the temporal semantic space, using manifold geometry to fully characterize the narrative rhythm and visual focus migration path of the display content. Then, a backlight topology mapping network maps these trajectory features end-to-end into multidimensional backlight control curve parameters while maintaining the local neighborhood and global distribution structure of the manifold. This ensures that the gradual changes and abrupt changes in the semantics of the display content are consistently reflected in the brightness and color temperature control of the backlight zones. Finally, a backlight synchronization control command sequence is generated that matches the narrative rhythm and visual focus migration path of the screen switching, realizing the continuous following and dynamic reconstruction of the spatiotemporal evolution of the semantics of the display content by the backlight emission distribution.

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