'Lying Mirror' Uses Structured Surfaces To Conceal Optical Information

Mirrors normally reveal what is placed in front of them, even when their curvature distorts a reflection. Researchers at the University of California, Los Angeles (UCLA) have introduced a different optical concept: a lying mirror that hides information carried by an input image and transforms it into a misleading, ordinary-looking pattern at the output.

The all-optical system combines a reflective mirror with an optimized structured diffractive surface. Instead of using a computer to digitally alter an image, the lying mirror performs the transformation through programmed light diffraction and passive light-matter interactions. Once the diffractive surface is designed and fabricated, the optical transformation that hides the input information itself requires no digital computation.

Using deep learning, the UCLA team optimized the phase profile of the structured surface so that many different and unknown input objects can be mapped to a predefined ‘dummy’ misleading output image. Tests on new image distributions not used during training further demonstrated external generalization beyond the original training datasets.

The system also remained functional when input objects were randomly rotated, shifted or scaled, and when image noise was added. These tests demonstrate the lying mirror’s ability to conceal a broad range of structured inputs rather than simply memorizing a set of input-output pairs.

“Instead of simply distorting a reflection, the lying mirror is designed to optically replace the visual information carried by many different, unknown inputs with a predefined deceptive pattern,” said Prof. Aydogan Ozcan. “This illustrates how a passive structured surface can perform sophisticated visual information processing directly through structured light matter interactions.”

The team experimentally validated the concept using a programmable micro-mirror array in the visible spectrum. Under red (R), green (G) and blue (B) illumination at 600, 550 and 480 nm, randomly selected objects that had not been used during training were successfully transformed into a predefined dummy output image, which in this case was a handwritten digit ‘8’. The researchers further developed a broadband lying mirror that operates across a continuous spectral range, extending the concept beyond discrete RGB illumination. Together, the multi-wavelength and broadband demonstrations support the feasibility of learned structured surfaces for optical concealment under diverse illumination conditions.

This lying mirror framework points to new possibilities for compact, passive optical information concealment and visual processing. Potential applications discussed by UCLA researchers include security, defense, anti-surveillance technologies and entertainment.

The study was supervised by Prof. Aydogan Ozcan of UCLA. The authors are Yuhang Li, Shiqi Chen, Bijie Bai and Aydogan Ozcan. Yuhang Li and Shiqi Chen contributed equally to the work.