Meta-DCP: simple and efficient single-frame image enhancement algorithm for infrared metalens images

Area of Science:

• Optics and Photonics
• Image Processing

Background:

• Infrared metalenses offer an alternative to traditional optical systems.
• Images from infrared metalenses often suffer from blur, aberrations, and noise.
• Existing enhancement methods may not be optimal for metalens-derived infrared imagery.

Purpose of the Study:

• To propose and validate Meta-DCP, a novel algorithm for infrared metalens image enhancement.
• To address the challenges of blur and noise in infrared metalens images.
• To improve the clarity and quality of images captured by infrared metalenses.

Main Methods:

• Developed an image degradation model specific to infrared metalens imaging.
• Applied the dark channel prior (DCP) principle for deblurring.
• Integrated a brightness enhancement technique preserving original image patterns.

Main Results:

• The proposed image degradation model effectively simulates infrared metalens image distortions.
• Meta-DCP successfully recovers deblurred images using the DCP.
• The integrated brightness enhancement compensates for luminance loss.
• Experimental results validate the effectiveness and superiority of Meta-DCP.

Conclusions:

• Meta-DCP provides a concise, single-frame solution for infrared metalens image enhancement.
• The algorithm significantly improves image quality by reducing blur and noise.
• Meta-DCP demonstrates superior performance compared to existing methods for infrared metalens imagery.