Spatial-temporal binarization encoding basis modulation Fourier single-pixel imaging.

Area of Science:

• Optics and Photonics
• Image Processing
• Computational Imaging

Background:

• Fourier single-pixel imaging (FSI) faces limitations in switching rates and binary encoding of sinusoidal features.
• Existing FSI methods struggle with efficient reconstruction and maintaining image quality.

Purpose of the Study:

• To present a novel FSI method using spatial-temporal binary encoding to overcome current limitations.
• To achieve rapid and high-quality image reconstruction in FSI.

Main Methods:

• Developed an innovative image extension algorithm for scene preprocessing.
• Decomposed grayscale Fourier basis patterns into binary patterns using dynamic thresholding and error diffusion.
• Implemented a weighted reconstruction strategy for efficient single-pixel measurements.

Main Results:

• Achieved substantial improvements in image reconstruction quality compared to existing techniques.
• Demonstrated significant enhancements in SSIM (up to 80%) and PSNR (up to 43%) for simple scenes.
• Showcased notable performance gains in complex scenes (SSIM up to 27.9%) and reduced RMSE.
• Reduced sampling time by up to 28.225s while maintaining comparable reconstruction quality to grayscale projections.

Conclusions:

• The proposed spatial-temporal binary encoding FSI method offers superior image reconstruction quality and efficiency.
• The method excels in preserving texture details and enhancing background reconstruction.
• This technique presents a versatile and practical advancement for diverse FSI applications.